Algorithms and data structures Books
Springer International Publishing AG Data Structures and Algorithms with Python: With
Book SynopsisThis textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms—supported by motivating examples—that bring meaning to the problems faced by computer programmers. The idea of computational complexity is introduced, demonstrating what can and cannot be computed efficiently at scale, helping programmers make informed judgements about the algorithms they use. The easy-to-read text assumes some basic experience in computer programming and familiarity in an object-oriented language, but not necessarily with Python.Topics and features: Includes introductory and advanced data structures and algorithms topics, with suggested chapter sequences for those respective courses Provides learning goals, review questions, and programming exercises in each chapter, as well as numerous examples Presents a primer on Python for those coming from a different language background Adds a new chapter on multiprocessing with Python using the DragonHPC multinode implementation of multiprocessing (includes a tutorial) Reviews the use of hashing in sets and maps, and examines binary search trees, tree traversals, and select graph algorithms Offers downloadable programs and supplementary files at an associated website to help students Students of computer science will find this clear and concise textbook invaluable for undergraduate courses on data structures and algorithms, at both introductory and advanced levels. The book is also suitable as a refresher guide for computer programmers starting new jobs working with Python.Dr. Kent D. Lee is a Professor Emeritus of Computer Science at Luther College, Decorah, Iowa, USA. He is the author of the successful Springer books, Python Programming Fundamentals, and Foundations of Programming Languages.Dr. Steve Hubbard is a Professor Emeritus of Mathematics and Computer Science at Luther College.Table of Contents1. Python Programming 101.- 2. Computational Complexity.- 3. Recursion.- 4. Sequences.- 5. Sets and Maps.- 6. Trees.- 7. Graphs.- 8. Membership Structures.- 9. Heaps.- 10. Balanced Binary Search Trees.- 11. B-Trees.- 12. Heuristic Search.
£40.49
Springer International Publishing AG Artificial Evolution: 15th International
Book SynopsisThis book constitutes the refereed post-conference proceedings of the 15th International Conference, Évolution Artificielle, EA 2022, held in Exeter, UK, during October 31–November 2, 2022.The 15 full papers were carefully reviewed and selected from 18 submissions. The papers cover a wide range of topics in the field of artificial evolution, including, but not limited to: evolutionary computation, evolutionary optimization, coevolution, artificial life, population dynamics, theory, algorithmic and modeling, implementations.Table of ContentsOn the Active Use of an ND-Tree-Based Archive for Multi-Objective Optimisation.- HyTEA: Hybrid Tree Evolutionary Algorithm.- A Game Theoretic Decision Tree for Binary Classification.- Evaluating a New Genetic Algorithm for Automated Machine Learning in Positive-Unlabelled Learning.- Neural Network-based Virtual Analog Modeling.- Defining a Quality Measure Within Crossover: An Electric Bus Scheduling Case Study.- Maximizing the Number of Satisfied Charging Demands in Electric Vehicle Charging Scheduling Problem.- Fine-Grained Cooperative Coevolution in a Single Population: Between Evolution and Swarm Intelligence.- One-Class Ant-Miner: Selection of Majority Class Rules for Binary Rule-based Classification.- Towards a Many-Objective Optimiser for University Course Timetabling.- Empirical Investigation of MOEAs for Multi-objective Design of Experiments.- Evolutionary Continuous Optimization of Hybrid Gene Regulatory Networks.- Designing Attention based Convolutional Neural Network (CNN) Architectures for Medical Image Classification using Genetic Algorithm based on Variable Length-encoding Scheme.- A Multi-objective 3D Offline UAV Path Planning Problem with Variable Flying Altitude.- An Elitist Non-dominated Heuristic Resolution for the Dynamic Asset Protection Problem.
£47.49
Springer International Publishing AG Bio-inspired Information and Communications
Book SynopsisThis book constitutes the refereed conference proceedings of the 14th International Conference on Bio-inspired Information and Communications Technologies, held in Okinawa, Japan, during April 11-12, 2023. The 17 full papers were carefully reviewed and selected from 33 submissions. The papers focus on the latest research that leverages the understanding of key principles, processes, and mechanisms in biological systems for development of novel information and communications technologies (bio-inspired ICT). BICT 2023 will also highlight innovative research and technologies being developed for biomedicine that are inspired by ICT (ICT-inspired biomedicine).Table of ContentsElectromagnetic-induced Calcium signal with network coding for molecular communications.- Smart Farm Teaching Aids based on STEM concepts.- Reinforcement Learning for Multifocal Tumour Targeting.- Automatic Soil Testing Device for Agriculture.- A Novel Visualization Method of Vessel Network for tumour Targeting: A Vessel Matrix Approach.- Heterogeneous Group of Fish Response to Escape Reaction.- Modeling and Simulation of a Bio-inspired Nanorobotic Drug Delivery System.- Cooperative Relaying in Multi-Hop Mobile Molecular Communication via Diffusion.- Covid-19 Versus Monkeypox-2022: The Silent Struggle of Global Pandemics.- Monte Carlo Simulation of Arbitrium and the Probabilistic Behavior of Bacteriophages.- Instant Messaging Application for 5G Core Network.- Genetic Algorithm-based Fair Order Assignment Optimization of Food Delivery Platform.- Preliminary Considerations on Non-Invasive Home-Based Bone Fracture Healing Monitoring.- Features of Audio Frequency Content of Respiration to Distinguish Inhalation from Exhalation.- Management of the medical file in case of emergency.- A Novel Durable Fat Tissue Phantom for Microwave Based Medical Monitoring Applications.- ISI Mitigation with Molecular Degradation in Molecular Communication.- Signal Transmission Through Human Body Via Human Oxygen Saturation Detection.- Simple ISI-Avoiding and Rate-Increasing Modulation for Diffusion-base Molecular Communications.- Range Expansion in Neuro-spike Synaptic Communication: Error Performance Analysis.- [Extended Abstract] Collective Bio-nanomachine Rotation via Chemical and Physical Interactions: A Three- dimensional Model.- Wearable Vibration Device to Assist with Ambulation for the Visually Impaired.- Development of Capacitive Sensors to Detect and Quantify Fluids in the Adult Diaper.- Energy Cyber Attacks to Smart Healthcare Devices: A Testbed.- [Extended Abstract] Wet-laboratory Experiments and Computer Simulation of Interacting Cell Spheroids.- Ensembles of Heuristics and Computational Optimisation In Highly Flexible Manufacturing System.- A Intelligent Nanorobots Fish Swarm Strategy for Tumor Targetting.- [Extended abstract] Design and Implementation of A General-purpose Multicellular Molecular Communication Simulator.
£61.74
Springer International Publishing AG Information and Communication Technologies: 11th
Book SynopsisThis book constitutes the proceedings of the 11th Ecuadorian Conference on Information and Communication Technologies, TICEC 2023, held in Cuenca, Ecuador, during October 18–20, 2023.The 31 full papers presented were carefully reviewed and selected from 120 submissions. The papers cover a great variety of topics, such as internet of things, cyber-physical systems, human-machine interface, artificial Intelligence, e-Learning, smart healthcare, smart healthcare and others. The papers are organized in the following topical sections: data science and machine learning; ICTs and their applications; and software development.Table of ContentsData Science and Machine Learning: Uncovering the Effects of the Russia-Ukraine Conflict on Cryptocurrencies: A Data-driven Analysis with Clustering and Biplot Techniques.- Human Trafficking in Social Networks: A Review of Machine Learning Techniques.- Exploring the Performance of Deep Learning in High-Energy Physics.- Human actions recognition system based on Neural Networks.- Big Data Architecture for Air Pollution Spatial Visualization: Quito, Ecuador.- The Role of Twitter in Media Coverage during Humanitarian Crises. Data mining from International News Agencies.- Applied Metaheuristics in International Trading: A Systematic Review.- Finding an Integrated Ultraviolet Radiation Index Using Fuzzy Logic Techniques.- Forecasting the Consumer Price Index of Ecuador using Classical and Advanced Time Series Models.- Forecasting PM2.5 concentrations in ambient air using a transformer based neural network.- Machine Learning Applied to the Analysis of Glacier Masses.- Profit vs Accuracy: Balancing the Impact on Users Introduced by Profit-Aware Recommender Systems.- Augmenting Data with DCGANs to Improve Skin Lesions Classification.- Unraveling the power of 4D residual blocks and transfer learning in violence detection.- ICTs and their Applications: Brainwaves communication system for people with reduced mobility and verbal impairment.- Advanced metrics to evaluate autistic children's attention and emotions from facial characteristics using a human-robot-game interface.- Performance analysis of You Only Look Once, RetinaNet, and Single Shot Detector applied to vehicle detection and counting.- Tumor kidney segmentation from CT images using residual U-net architecture.- Classification of Alzheimer disease’s Severity Using Support Vector Machine and Deep Feature Extraction of Convolutional Neural Networks: a Contrasting of Methodologies.- Creation of an alert device for early detection of epilepsy using an EEG signal power threshold.- Optimal location of the electric vehicle charging stands using multi-objective evolutionary algorithms: Cuenca city as a case study.- Detecting Parkinson’s Disease with Convolutional Neural Networks: Voice Analysis and Deep Learning.- Hyperparameter Tuning in a Dual Channel U-Net for Medical Image Segmentation.- Vitreous Hemorrhage Segmentation in Fundus Images by using an Efficient-UNet Network.- A non-invasive portable solution to estimate hemoglobin levels in the blood.- Mask R-CNN and YOLOv8 comparison to perform tomato maturity recognition task.- Software Development.- Development of a distributed hydrological model of continuous generation, in a GIS environment.- A Domain-Specific Language and Model-Based Engine for Implementing IoT Dash- board Web Applications.- Feasibility of using serious MIDI-AM videogames as resources in early childhood education.- Search and Visualization of Researcher Networks: Co-authorship in Ecuador.- Visualization Models Applied to Atmospheric Pollutants and Meteorological Variables: A Systematic Literature Review.
£71.24
Springer International Publishing AG Software Engineering and Formal Methods: 21st
Book SynopsisThis book constitutes the refereed proceedings of the 21st International Conference on Software Engineering and Formal Methods, SEFM 2023, held in Eindhoven, The Netherlands, during November 6-10, 2023. The 18 regular papers presented in this book, together with 1 invited paper and 1 tool paper, were carefully reviewed and selected from 41 submissions. The SEFM conference series aims to bring together researchers and practitioners from academia, industry and government, to advance the state of the art in formal methods, to facilitate their uptake in the software industry, and to encourage their integration within practical software engineering methods and tools.Table of ContentsRefinements for Open Automata.- The Cubicle Fuzzy Loop : A Fuzzing-Based Extension for the Cubicle Model Checker.- Guiding Symbolic Execution with A-star.- Robustness Testing of Software Verifiers.- Decoupled Fitness Criteria for Reactive Systems.- Capturing Smart Contract Design with DCR Graphs.- An Active Learning Approach to Synthesizing Program Contracts.- Ranged Program Analysis via Instrumentation.- Attack time analysis in dynamic attack trees via integer linear programming.- SSCalc A Calculus for Solidity Smart Contracts.- ATM: a Logic for Quantitative Security Properties on Attack Trees.- Refactoring of Multi-Instance BPMN Processes with Time and Resources.- Verified Scalable Parallel Computing with Why3.- Exact and Efficient Bayesian Inference for Privacy Risk Quantification.- A Formalization of Heisenbugs and Their Causes.- Verifying Read-Copy Update under RC11.- QNNRepair: Quantized Neural Network Repair.- Timeout Prediction for Software Analyses.- PART Tool Papers.- PMC-VIS: An Interactive Visualization Tool for Probabilistic Model Checking.
£49.49
Springer International Publishing AG Conceptual Modeling: 42nd International
Book SynopsisThis book constitutes the refereed proceedings of the 42nd International Conference on Conceptual Modeling, ER 2023, held in Lisbon, Portugal, during November 6-9, 2023. The 21 full papers were carefully reviewed and selected from 121 submissions. Additionally, the book contains 4 keynote speeches and 3 tutorials, and one invited paper corresponding to one of the keynote speeches. The papers cover a broad spectrum of classical and modern topics on conceptual modeling, including research and practice in the theories of concepts and ontologies, techniques for transforming conceptual models into effective implementations, and methods and tools for developing and communicating conceptual models.Table of ContentsInvited Paper.- Stochastic LLMs do not Understand Language: Towards Symbolic, Explainable and Ontologically Based LLMs.- The Conceptual Modeling Task.- A Survey of Ethical Reasoning Methods, their Metamodels, and a Theory on their Application to Conceptual Modelling.- Use of Competency Questions in Ontology Engineering: a Survey.- How Inclusive is Conceptual Modeling? A Systematic Review of Literature and Tools for Disability-aware Conceptual Modeling.- The Meta Level.- A Terminological and Semiotic Review of the Digital Object Concept.- The Ontology for Conceptual Characterization of Ontologies.- ProMoTe: A Data Product Model Template for Industry.- Model-Based Analysis and Implementation.- Using a Conceptual Model in Plug-and-play SQL.- Sanity-Checking Multiple Levels of Classification – A Formal Approach with a ConceptBase Implementation.- A Safari for Deviating GoF Pattern Definitions and Examples on the Web.- Process Mining and Abstraction.- Object-Centric Alignments.- Transforming Event Knowledge Graph to Object-Centric Event Logs: A Comparative Study for Multi-dimensional Process Analysis.- Ontology-Based Abstraction of Bot Models in Robotic Process Automation.- Modeling Events and Processes.- Shards of Knowledge – Modeling Attributions for Event-Centric Knowledge Graphs.- A Characterisation of Ambiguity in BPM.- Dealing with the evolution of event-based choreographies of BPMN fragments: definition and proof of concept.- Conceptual Modeling in Context.- Safety Analysis of Human Robot Collaborations with GRL Goal Models.- A Domain-Specific Visual Modeling Language for Augmented Reality Applications Using WebXR.- An Ontology for Context Modeling in Smart Spaces.- Applications of Conceptual Modeling.- A Reference Meta-Model to Understand DNA Variant Interpretation Guidelines.- A Conceptual Modeling Approach for Risk Assessment and Mitigation in Collision-free UAV Routing for Beyond-the-Visual-Line-of-Sight Flights.- QuantumShare: Towards An Ontology for Bridging the Quantum Divide.
£61.74
Springer International Publishing AG Algorithmic Aspects of Cloud Computing: 8th
Book SynopsisThis book constitutes revised selected papers from the 8th International Symposium on Algorithmic Aspects of Cloud Computing, ALGOCLOUD 2023, held in Amsterdam, The Netherlands, on September 5, 2023. The 13 full papers included in this book were carefully reviewed and selected from 24 submissions. They focus on algorithmic aspects of computing and data management in modern cloud-based systems interpreted broadly so as to include edge- and fog-based systems, cloudlets, cloud micro-services, virtualization environments, decentralized systems, as well as dynamic networks.Table of ContentsPlanning workflow executions over the Edge-to-Cloud Continuum.- On-Field Leaf Infection Detection using the Cloud-Edge Continuum.- Application of Federated Learning techniques for arrhythmia classification using 12- lead ECG signals.- An Adaptive, Energy-Efficient DRL-based and MCMC-based Caching Strategy for IoT Systems.- Real-Time Leakage Zone Detection in Water Distribution Networks: A Machine Learning-based Stream Processing Algorithm.- Multi-agent reinforcement learning-based energy orchestrator for cyber-physical systems.- Clustering-based Numerosity Reduction for Cloud Workload Forecasting.- Algorithmic Aspects of Distributed Hash Tables on Cloud, Fog, and Edge Computing Applications: A Survey.- i-Deliver P&D Engine: A Decentralized Middleware for a Delivery-as-a-Service System.- Intent-based Allocation of Cloud Computing Resources Using Q-Learning.- A Double-decision Reinforcement Learning based Algorithm for Online Scheduling in Edge and Fog Computing.- Decentralized Algorithms for Efficient Energy Management over Cloud-Edge Infrastructures.
£47.49
Springer International Publishing AG Combinatorial Optimization and Applications: 16th
Book SynopsisThe two-volume set LNCS 14461 and LNCS 14462 constitutes the refereed proceedings of the 17th International Conference on Combinatorial Optimization and Applications, COCOA 2023, held in Hawaii, HI, USA, during December 15–17, 2023. The 73 full papers included in the proceedings were carefully reviewed and selected from 117 submissions. They were organized in topical sections as follows: Part I: Optimization in graphs; scheduling; set-related optimization; applied optimization and algorithm; Graph planer and others;Part II: Modeling and algorithms; complexity and approximation; combinatorics and computing; optimization and algorithms; extreme graph and others; machine learning, blockchain and others.Table of ContentsModeling and Algorithms.- Differentiable Discrete Optimization using Dataless Neural Networks.- When Advertising meets Assortment Planning: Joint Advertising and Assortment Optimization under Multinomial Logit Model.- Twin-treewidth: A single-exponential logic-based approach.- Highway Preferential Attachment Models for Geographic Routing.- Complexity and Approximation.- Restricted Holant Dichotomy on Domains 3 and 4.- Earliest Deadline First is a $2$-approximation for DARP with Time Windows.- Improved approximation for broadcasting in k-Path Graphs.- The fine-grained complexity of approximately counting proper connected colorings (extended abstract).- Combinatorics and Computing.- Strong edge coloring of subquartic graphs.- Two multicolor Ramsey numbers involving bipartite graphs.- Mechanism Design for Time-Varying Value Tasks in High-Load Edge Computing Markets.- Computing random r-orthogonal Latin squares.- Optimization and Algorithms.- A Two-stage Seeds Algorithm for Competitive Influence Maximization considering User Demand.- Practical Attribute-Based Multi-Keyword Search Scheme with Sensitive Information Hiding for Cloud Storage Systems.- Testing Higher-order Clusterability on graphs.- The $2$-mixed-center color spanning problem.- A Dynamic Parameter Adaptive Path Planning Algorithm.- On the Mating Between a Polygonal Curve and a Convex Polygon.- A Faster Parameterized Algorithm for Bipartite 1-Sided Vertex Explosion.- Multi-Winner Approval Voting with Grouped Voters.- EFX Allocation to Chores Over Small Graph.- Extreme Graph and Others.- Zero-visibility Cops and Robber game on Cage graph.- Online Facility Assignment for General Layout of Servers on a Line.- Guarding Precise and Imprecise Polyhedral Terrains with Segments.- The Bag-Based Search: A meta-algorithm to construct tractable logical circuits for graphs based on tree decomposition.- On Problems Related to Absent Subsequences.- Some Combinatorial Algorithms on the Dominating Number of Anti-Rank k Hypergraphs.- Parameterized and exact-exponential algorithms for the read-once integer refutation problem in UTVPI constraints.- Critical $(P_5,dart)$-Free Graphs.- Graph Clustering through Users' Properties and Social Influence.- Machine Learning, Blockchain and Others.- Incorporating Neural Point Process-based Temporal Feature for Rumor Detection.- Improving Contraction Hierarchies by Combining with All-Pairs Shortest Paths Problem Algorithms.- Information Theory of Blockchain Systems.- Machine Learning with Low Resource Data from Psychiatric Clinics.- Single Image Dehazing Based on Dynamic Convolution and Transformer.- Reinforcement Learning for Combating Cyberbullying in Online Social Networks.
£61.74
Springer International Publishing AG Formal Aspects of Component Software: 19th
Book SynopsisThis book constitutes the refereed proceedings of the 19th International Conference on Formal Aspects of Component Software, FACS 2023, which took place virtually during October 19-20, 2023.The 11 full papers included in this book were carefully reviewed and selected from 23 submissions. They were organized in topical sections as follows: cloud computing, cyber-physical and critical systems, and the Internet of Things.Table of ContentsResearch Papers.- Symbolic Path-guided Test Cases for Models with Data and Time.- Model-Based Testing of Asynchronously Communicating Distributed Controllers.- A Mechanized Semantics for Component-based Systems in the HAMR AADL Runtime.- A Formal Web Services Architecture Model for Changing PUSH/PULL Data Transfer.- Joint use of SysML and Reo to specify and verify the compatibility of CPS components.- From Reversible Computation to Checkpoint-Based Rollback Recovery for Message-Passing Concurrent Programs.- Anniversary Papers.- Formal Model Engineering of Distributed CPSs using AADL: From Behavioral AADL Models to Multirate Hybrid Synchronous AADL.- Challenges Engaging Formal CBSE in Industrial Applications.- Formal Aspects of Component Software - An Overview on Concepts and Relations of Different Theories.- Overview on Constrained Multiparty Synchronisation in Team Automata.- Embedding Formal Verification in Model-Driven Software Engineering with SLCO: An Overview.
£47.49
Springer Nature Switzerland Basics of Programming and Algorithms Principles
Book SynopsisThis textbook offers an introduction to topics in algorithms and programming with python.
£44.99
Springer Twenty Years of Theoretical and Practical
Book Synopsis.- Invited abstracts..- Special Session: Computing Knowledge: Computational Aspects of Epistemic Logics (HaPoC)..- The theory of enumeration degrees and its fragments..- Further extensions of the point to set principle..- Uniform distribution and algorithmic randomness..- Computable aspects of symbolic dynamics and tilings..- How much pattern complexity can help us solve the domino problem ?..- Sufficient conditions for non-emptiness of a subshift and computability of its entropy..- Reasoning about (Negative) Trust under Uncertainty..- Quantum computating from reversible classical computing..- Complexity of well-ordered sets in an ordered Abelian group..- Invited papers..- If CiE Did not Exist, It Would be Necessary to Invent It..- Some Open Questions and Recent Results on Computable Banach Spaces..- Kolmogorov complexity as a combinatorial tool..- Cellular Automata: Communicati
£61.74
Springer Advances in Computing and Data Sciences
Book SynopsisThis book constitutes the refereed proceedings of the 8th International Conference on Advances in Computing and Data Sciences, ICACDS 2024, held in Velizy, France, during May 910, 2024. The 28 full papers present here, were carefully reviewed and selected from 174 submissions.
£58.49
Springer String Processing and Information Retrieval
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£49.49
De Gruyter Data structures based on linear relations
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£44.25
De Gruyter Artificial Intelligence for Data-Driven Medical
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£85.12
De Gruyter Data structures based on non-linear relations and
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£44.25
De Gruyter Nature-Inspired Optimization Algorithms: Recent
Book SynopsisThis book will focus on the involvement of data mining and intelligent computing methods for recent advances in Biomedical applications and algorithms of nature-inspired computing for Biomedical systems. The proposed meta heuristic or nature-inspired techniques should be an enhanced, hybrid, adaptive or improved version of basic algorithms in terms of performance and convergence metrics. In this exciting and emerging interdisciplinary area a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging problems. Today, analysis and processing of data is one of big focuses among researchers community and information society. Due to evolution and knowledge discovery of natural computing, related meta heuristic or bio-inspired algorithms have gained increasing popularity in the recent decade because of their significant potential to tackle computationally intractable optimization dilemma in medical, engineering, military, space and industry fields. The main reason behind the success rate of nature inspired algorithms is their capability to solve problems. The nature inspired optimization techniques provide adaptive computational tools for the complex optimization problems and diversified engineering applications. Tentative Table of Contents/Topic Coverage: - Neural Computation - Evolutionary Computing Methods - Neuroscience driven AI Inspired Algorithms - Biological System based algorithms - Hybrid and Intelligent Computing Algorithms - Application of Natural Computing - Review and State of art analysis of Optimization algorithms - Molecular and Quantum computing applications - Swarm Intelligence - Population based algorithm and other optimizations
£85.12
De Gruyter Algorithms: Design and Analysis
Book SynopsisAlgorithms play a central role both in the theory and in the practice of computing. The goal of the authors was to write a textbook that would not trivialize the subject but would still be readable by most students on their own. The book contains over 120 exercises. Some of them are drills; others make important points about the material covered in the text or introduce new algorithms not covered there. The book also provides programming projects. From the Table of Contents: Chapter 1: Basic knowledge of Mathematics, Relations, Recurrence relation and Solution techniques, Function and Growth of functions. Chapter 2: Different Sorting Techniques and their analysis. Chapter 3: Greedy approach, Dynamic Programming, Branch and Bound techniques, Backtracking and Problems, Amortized analysis, and Order Statics. Chapter 4: Graph algorithms, BFS, DFS, Spanning Tree, Flow Maximization Algorithms. Shortest Path Algorithms. Chapter 5: Binary search tree, Red black Tree, Binomial heap, B-Tree and Fibonacci Heap. Chapter 6: Approximation Algorithms, Sorting Networks, Matrix operations, Fast Fourier Transformation, Number theoretic Algorithm, Computational geometry Randomized Algorithms, String matching, NP-Hard, NP-Completeness, Cooks theorem.
£37.12
De Gruyter Blockchain 3.0 for Sustainable Development
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£85.12
Walter de Gruyter Maschinelles Lernen
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£59.85
De Gruyter Computer Intelligence Against Pandemics: Tools
Book SynopsisThis book introduces the most recent research and innovative developments regarding the new strains of COVID-19. While medical and natural sciences have been working instantly on deriving solutions and trying to protect humankind against such virus types, there is also a great focus on technological developments for improving the mechanism – momentum of science for effective and efficient solutions. At this point, computational intelligence is the most powerful tools for researchers to fight against COVID-19. Thanks to instant data-analyze and predictive techniques by computational intelligence, it is possible to get positive results and introduce revolutionary solutions against related medical diseases. By running capabilities – resources for rising the computational intelligence, technological fields like Artificial Intelligence (with Machine / Deep Learning), Data Mining, Applied Mathematics are essential components for processing data, recognizing patterns, modelling new techniques and improving the advantages of the computational intelligence more. Nowadays, there is a great interest in the application potentials of computational intelligence to be an effective approach for taking humankind more step away, after COVID-19 and before pandemics similar to the COVID-19 many appear.
£137.28
de Gruyter Modern Algorithms for Large Sparse Eigenvalue
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£111.62
de Gruyter Bericht Über Die Algorithmische Sprache ALGOL 60
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£134.09
De Gruyter Algorithmen und rekursive Funktionen
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£134.09
de Gruyter Algebra Sprachen Programmierung
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£134.09
Springer International Publishing AG Convex Optimization in Normed Spaces: Theory, Methods and Examples
Book SynopsisThis work is intended to serve as a guide for graduate students and researchers who wish to get acquainted with the main theoretical and practical tools for the numerical minimization of convex functions on Hilbert spaces. Therefore, it contains the main tools that are necessary to conduct independent research on the topic. It is also a concise, easy-to-follow and self-contained textbook, which may be useful for any researcher working on related fields, as well as teachers giving graduate-level courses on the topic. It will contain a thorough revision of the extant literature including both classical and state-of-the-art references.Trade Review“This short book is dedicated to convex optimization, beginning with theoretical aspects, ending with numerical methods, and complemented with numerous examples. … this is an interesting and well-written book that is adequate for a graduate-level course on convex optimization.” (Constantin Zălinescu, Mathematical Reviews, November, 2015)Table of ContentsBasic Functional Analysis.- Existence of Minimizers.- Convex Analysis and Subdifferential Calculus.- Examples.- Problem-solving Strategies.- Keynote Iterative Methods.
£41.24
Springer International Publishing AG Parameterized Algorithms
Book SynopsisThis comprehensive textbook presents a clean and coherent account of most fundamental tools and techniques in Parameterized Algorithms and is a self-contained guide to the area. The book covers many of the recent developments of the field, including application of important separators, branching based on linear programming, Cut & Count to obtain faster algorithms on tree decompositions, algorithms based on representative families of matroids, and use of the Strong Exponential Time Hypothesis. A number of older results are revisited and explained in a modern and didactic way.The book provides a toolbox of algorithmic techniques. Part I is an overview of basic techniques, each chapter discussing a certain algorithmic paradigm. The material covered in this part can be used for an introductory course on fixed-parameter tractability. Part II discusses more advanced and specialized algorithmic ideas, bringing the reader to the cutting edge of current research. Part III presents complexity results and lower bounds, giving negative evidence by way of W[1]-hardness, the Exponential Time Hypothesis, and kernelization lower bounds.All the results and concepts are introduced at a level accessible to graduate students and advanced undergraduate students. Every chapter is accompanied by exercises, many with hints, while the bibliographic notes point to original publications and related work.Trade Review“I enjoyed reading this book, which is a good textbook for graduate and advanced undergraduate students of computer science. Each chapter contains sufficient exercises with hints whenever necessary and helpful bibliographic notes. I found the references quite comprehensive, and the index was quite useful. … this is the best book I have seen on the topic. I strongly recommend it.” (Soubhik Chakraborty, Computing Reviews, April, 2017)“The style of the book is clear, and the material is well positioned to be accessible by graduate students and advanced undergraduate students. The exercises and hints provide a good ground for self-study, while bibliographic notes point to original papers and related work. Overall, this is an excellent book that can be useful to graduate and advanced undergraduate students either as a self-study text or as part of a course.” (Alexander Tzanov, Computing Reviews, February, 2016)“This is the most recent and most up-to-date textbook on parameterized algorithms, one of the major thrusts in algorithmics in recent years. … this new textbook has more than twice as many pages shows the development of the field. … This book does a very good job at balancing the necessary mathematical rigour with a nice presentation of the results.” (Henning Fernau, Mathematical Reviews, February, 2016)“This book serves as an introduction to the field of parameterized algorithms and complexity accessible to graduate students and advanced undergraduate students. It contains a clean and coherent account of some of the most recent tools and techniques in the area.” (Paulo Mbunga, zbMATH 1334.90001, 2016)Table of ContentsIntroduction.- Kernelization.- Bounded Search Trees.- Iterative Compression.- Randomized Methods in Parameterized Algorithms.- Miscellaneous.- Treewidth.- Finding Cuts and Separators.- Advanced Kernelization Algorithms.- Algebraic Techniques: Sieves, Convolutions, and Polynomials.- Improving Dynamic Programming on Tree Decompositions.- Matroids.- Fixed-Parameter Intractability.- Lower Bounds Based on the Exponential-Time Hypothesis.- Lower Bounds for Kernelization.
£56.99
Springer International Publishing AG Cryptography Made Simple
Book SynopsisIn this introductory textbook the author explains the key topics in cryptography. He takes a modern approach, where defining what is meant by "secure" is as important as creating something that achieves that goal, and security definitions are central to the discussion throughout.The author balances a largely non-rigorous style — many proofs are sketched only — with appropriate formality and depth. For example, he uses the terminology of groups and finite fields so that the reader can understand both the latest academic research and "real-world" documents such as application programming interface descriptions and cryptographic standards. The text employs colour to distinguish between public and private information, and all chapters include summaries and suggestions for further reading.This is a suitable textbook for advanced undergraduate and graduate students in computer science, mathematics and engineering, and for self-study by professionals in information security. While the appendix summarizes most of the basic algebra and notation required, it is assumed that the reader has a basic knowledge of discrete mathematics, probability, and elementary calculus.Trade Review“The goal of cryptography is to obfuscate data for unintended recipients. … The book is divided into four parts. … The book is very comprehensive, and very accessible for dedicated students.” (Klaus Galensa, Computing Reviews, computingreviews.com, October, 2016)“Cryptography made simple is a textbook that provides a broad coverage of topics that form an essential working knowledge for the contemporary cryptographer. It is particularly suited to introducing graduate and advanced undergraduate students in computer science to the concepts necessary for understanding academic cryptography and its impact on real-world practice, though it will also be useful for mathematicians or engineers wishing to gain a similar perspective on this material.” (Maura Beth Paterson, Mathematical Reviews, July, 2016)“This is a very thorough introduction to cryptography, aimed at lower-division undergraduates. It is an engineering textbook that uses modern mathematical terminology (such as groups and finite fields). … Bottom line: really for engineers, and a useful book if used carefully; the organization makes is easy to get overwhelmed by the background material before you get to the 'good stuff', and even the good stuff has an overwhelming amount of detail.” (Allen Stenger, MAA Reviews, maa.org, June, 2016)“This very thorough book by Smart (Univ. of Bristol, UK) is aimed at graduate students and advanced undergraduates in mathematics and computer science and intended to serve as a bridge to research papers in the field. … Summing Up: Recommended. Upper-division undergraduates through professionals/practitioners.” (C. Bauer, Choice, Vol. 53 (10), June, 2016)Table of ContentsModular Arithmetic, Groups, Finite Fields and Probability.- Elliptic Curves.- Historical Ciphers.- The Enigma Machine.- Information Theoretic Security.- Historical Stream Ciphers.- Modern Stream Ciphers.- Block Ciphers.- Symmetric Key Distribution.- Hash Functions and Message Authentication Codes.- Basic Public Key Encryption Algorithms.- Primality Testing and Factoring.- Discrete Logarithms.- Key Exchange and Signature Schemes.- Implementation Issues.- Obtaining Authentic Public Keys.- Attacks on Public Key Schemes.- Definitions of Security.- Complexity Theoretic Approaches.- Provable Security: With Random Oracles.- Hybrid Encryption.- Provable Security: Without Random Oracles.- Secret Sharing Schemes.- Commitments and Oblivious Transfer.- Zero-Knowledge Proofs.- Secure Multiparty Computation.
£37.85
Springer International Publishing AG Secure Data Deletion
Book SynopsisThis book is the first to develop a systematized approach for the comparison and evaluation of secure deletion solutions. The book focuses on novel secure deletion solutions targeting specific real-world environments where secure deletion is problematic: mobile storage and remote storage. The author surveys related work, organizes existing solutions in terms of their interfaces, presents a taxonomy of adversaries differing in their capabilities, and then builds a system and adversarial model based on the survey of related work.The book is useful for both academics, researchers and graduate students, and for practitioners who may integrate its results into deployed systems.Trade Review“In this book, the author discusses all of this, as well as some of the ways to ensure secure deletion … . The material is generally well presented and interesting … . This book could well be used as supplemental material for an undergraduate course in computer security or in operating systems, as the author mentions implementations in Linux for several ideas presented.” (Computing Reviews, May, 2017)Table of ContentsIntroduction.- Related Work on Secure Deletion.- System Model and Security Goal.- Flash Memory: Background and Related Work.- User-Level Secure Deletion on Log-Structured File Systems.- Data Node Encrypted File System.- UBIFSec: Adding DNEFS to UBIFS.- Cloud Storage: Background and Related Work.- Secure Data Deletion from Persistent Media.- B-Tree-Based Secure Deletion.- Robust Key Management for Secure Data Deletion.- Conclusions.
£87.99
Springer International Publishing AG A Guide to Graph Colouring: Algorithms and
Book SynopsisThis book treats graph colouring as an algorithmic problem, with a strong emphasis on practical applications. The author describes and analyses some of the best-known algorithms for colouring arbitrary graphs, focusing on whether these heuristics can provide optimal solutions in some cases; how they perform on graphs where the chromatic number is unknown; and whether they can produce better solutions than other algorithms for certain types of graphs, and why. The introductory chapters explain graph colouring, and bounds and constructive algorithms. The author then shows how advanced, modern techniques can be applied to classic real-world operational research problems such as seating plans, sports scheduling, and university timetabling. He includes many examples, suggestions for further reading, and historical notes, and the book is supplemented by a website with an online suite of downloadable code. The book will be of value to researchers, graduate students, and practitioners in the areas of operations research, theoretical computer science, optimization, and computational intelligence. The reader should have elementary knowledge of sets, matrices, and enumerative combinatorics.Trade Review“The book gives a comprehensive description and handling on arguably one of the most important notions of combinatorics—graph coloring. … The book is nicely written, and carries a big pile of information valuable for both users and researchers in the field.” (András Sándor Pluhár, Mathematical Reviews, February, 2017)“This well-written book will serve as a utilitarian guide to graph coloring and its practical applications. It includes many definitions, theorems, proofs, algorithms, and pointers for further reading. The book will be helpful for teaching courses on graph coloring to students of mathematics and computer science. I strongly recommend it for the intended audience.” (S. V. Nagaraj, Computing Reviews, computingreviews.com, June, 2016)“The book is a comprehensive guide to graph colouring algorithms. … The book is a nice textbook for both undergraduate and graduate students in the areas of operations research and theoretical computer science. … Finally, it is a good source of knowledge for practitioners.” (Marcin Anholcer, zbMATH 1330.05002, 2016)Table of ContentsIntroduction to Graph Colouring.- Bounds and Constructive Algorithms.- Advanced Techniques for Graph Colouring.- Algorithm Case Studies.- Applications and Extensions.- Designing Seating Plans.- Designing Sports Leagues.- Designing University Timetables.- App. A, Computing Resources.- References.- Index.
£75.99
Springer International Publishing AG Convex Analysis and Monotone Operator Theory in
Book SynopsisThis reference text, now in its second edition, offers a modern unifying presentation of three basic areas of nonlinear analysis: convex analysis, monotone operator theory, and the fixed point theory of nonexpansive operators. Taking a unique comprehensive approach, the theory is developed from the ground up, with the rich connections and interactions between the areas as the central focus, and it is illustrated by a large number of examples. The Hilbert space setting of the material offers a wide range of applications while avoiding the technical difficulties of general Banach spaces. The authors have also drawn upon recent advances and modern tools to simplify the proofs of key results making the book more accessible to a broader range of scholars and users. Combining a strong emphasis on applications with exceptionally lucid writing and an abundance of exercises, this text is of great value to a large audience including pure and applied mathematicians as well as researchers in engineering, data science, machine learning, physics, decision sciences, economics, and inverse problems. The second edition of Convex Analysis and Monotone Operator Theory in Hilbert Spaces greatly expands on the first edition, containing over 140 pages of new material, over 270 new results, and more than 100 new exercises. It features a new chapter on proximity operators including two sections on proximity operators of matrix functions, in addition to several new sections distributed throughout the original chapters. Many existing results have been improved, and the list of references has been updated.Heinz H. Bauschke is a Full Professor of Mathematics at the Kelowna campus of the University of British Columbia, Canada.Patrick L. Combettes, IEEE Fellow, was on the faculty of the City University of New York and of Université Pierre et Marie Curie – Paris 6 before joining North Carolina State University as a Distinguished Professor of Mathematics in 2016.Table of Contents
£93.60
Springer International Publishing AG Simulation Algorithms for Computational Systems
Book SynopsisThis book explains the state-of-the-art algorithms used to simulate biological dynamics. Each technique is theoretically introduced and applied to a set of modeling cases. Starting from basic simulation algorithms, the book also introduces more advanced techniques that support delays, diffusion in space, or that are based on hybrid simulation strategies.This is a valuable self-contained resource for graduate students and practitioners in computer science, biology and bioinformatics. An appendix covers the mathematical background, and the authors include further reading sections in each chapter.Trade Review“I will not hesitate to recommend … this book, both as an introductory explanation as well as later on when they are deep in a modeling exercise and need to understand the many subtle yet important variations of stochastic simulation techniques applicable to biological systems.” (Sara Kalvala, Computing Reviews, March, 2018)Table of ContentsIntroduction.- Deterministic Simulation Algorithms.- Stochastic Simulation Algorithms.- Hybrid Simulation Algorithms.- Reaction-Diffusion Systems.- Conclusions and Perspectives.
£34.49
Springer International Publishing AG Guide to Data Structures: A Concise Introduction
Book SynopsisThis accessible and engaging textbook/guide provides a concise introduction to data structures and associated algorithms. Emphasis is placed on the fundamentals of data structures, enabling the reader to quickly learn the key concepts, and providing a strong foundation for later studies of more complex topics. The coverage includes discussions on stacks, queues, lists, (using both arrays and links), sorting, and elementary binary trees, heaps, and hashing. This content is also a natural continuation from the material provided in the separate Springer title Guide to Java by the same authors.Topics and features: reviews the preliminary concepts, and introduces stacks and queues using arrays, along with a discussion of array-based lists; examines linked lists, the implementation of stacks and queues using references, binary trees, a range of varied sorting techniques, heaps, and hashing; presents both primitive and generic data types in each chapter, and makes use of contour diagrams to illustrate object-oriented concepts; includes chapter summaries, and asks the reader questions to help them interact with the material; contains numerous examples and illustrations, and one or more complete program in every chapter; provides exercises at the end of each chapter, as well as solutions to selected exercises, and a glossary of important terms.This clearly-written work is an ideal classroom text for a second semester course in programming using the Java programming language, in preparation for a subsequent advanced course in data structures and algorithms. The book is also eminently suitable as a self-study guide in either academe or industry.Trade Review“This text is intended to provide undergraduates using Java with a concise, focused, and relatively simple coverage of some of the basic data structures in use. These include arrays, linked lists, trees, heaps (in arrays), and hash tables. … The book covers the algorithms and data structures well with clear language, abundant diagrams, and good exercises. It could be a good introduction for curricula using Java as a primary teaching language.” (Jeffrey Putnam, Computing Reviews, July, 2018)Table of ContentsPreliminary Concepts Stacks Using Arrays Queues Using Arrays Lists Using Arrays Lists Using Objects and References Ordered Linked Lists Stacks and Queues Using References Binary Trees Sorting Heaps Hashing
£36.95
Springer International Publishing AG Convex Analysis and Monotone Operator Theory in
Book SynopsisThis reference text, now in its second edition, offers a modern unifying presentation of three basic areas of nonlinear analysis: convex analysis, monotone operator theory, and the fixed point theory of nonexpansive operators. Taking a unique comprehensive approach, the theory is developed from the ground up, with the rich connections and interactions between the areas as the central focus, and it is illustrated by a large number of examples. The Hilbert space setting of the material offers a wide range of applications while avoiding the technical difficulties of general Banach spaces. The authors have also drawn upon recent advances and modern tools to simplify the proofs of key results making the book more accessible to a broader range of scholars and users. Combining a strong emphasis on applications with exceptionally lucid writing and an abundance of exercises, this text is of great value to a large audience including pure and applied mathematicians as well as researchers in engineering, data science, machine learning, physics, decision sciences, economics, and inverse problems. The second edition of Convex Analysis and Monotone Operator Theory in Hilbert Spaces greatly expands on the first edition, containing over 140 pages of new material, over 270 new results, and more than 100 new exercises. It features a new chapter on proximity operators including two sections on proximity operators of matrix functions, in addition to several new sections distributed throughout the original chapters. Many existing results have been improved, and the list of references has been updated.Heinz H. Bauschke is a Full Professor of Mathematics at the Kelowna campus of the University of British Columbia, Canada.Patrick L. Combettes, IEEE Fellow, was on the faculty of the City University of New York and of Université Pierre et Marie Curie – Paris 6 before joining North Carolina State University as a Distinguished Professor of Mathematics in 2016.Table of Contents
£93.60
Springer International Publishing AG Lectures on Convex Optimization
Book SynopsisThis book provides a comprehensive, modern introduction to convex optimization, a field that is becoming increasingly important in applied mathematics, economics and finance, engineering, and computer science, notably in data science and machine learning. Written by a leading expert in the field, this book includes recent advances in the algorithmic theory of convex optimization, naturally complementing the existing literature. It contains a unified and rigorous presentation of the acceleration techniques for minimization schemes of first- and second-order. It provides readers with a full treatment of the smoothing technique, which has tremendously extended the abilities of gradient-type methods. Several powerful approaches in structural optimization, including optimization in relative scale and polynomial-time interior-point methods, are also discussed in detail. Researchers in theoretical optimization as well as professionals working on optimization problems will find this book very useful. It presents many successful examples of how to develop very fast specialized minimization algorithms. Based on the author’s lectures, it can naturally serve as the basis for introductory and advanced courses in convex optimization for students in engineering, economics, computer science and mathematics.Trade Review“It is a must-read for both students involved in the operations research programs, as well as the researchers in the area of nonlinear programming, in particular in convex optimization.” (Marcin Anholcer, zbMATH 1427.90003, 2020)Table of ContentsIntroduction.- Part I Black-Box Optimization.- 1 Nonlinear Optimization.- 2 Smooth Convex Optimization.- 3 Nonsmooth Convex Optimization.- 4 Second-Order Methods.- Part II Structural Optimization.- 5 Polynomial-time Interior-Point Methods.- 6 Primal-Dual Model of Objective Function.- 7 Optimization in Relative Scale.- Bibliographical Comments.- Appendix A. Solving some Auxiliary Optimization Problems.- References.- Index.
£49.49
Springer Fachmedien Wiesbaden Komplexitätstheorie Band I: Grundlagen:
Book SynopsisDie Komplexitätstheorie untersucht den algorithmischen Aufwand zur Lösung von Problemen mit Hilfe einer Maschine. Dabei werden Rechnermodelle wie Turing-Maschinen oder Registermaschinen verwendet, um von speziellen Architektur- und Implementationsdetails unabhängige Ergebnisse zu gewinnen.Table of Contents1 Das TM-Modell.- 1.0 Vorbemerkungen.- 1.0.1 Mengen.- 1.0.2 Graphen.- 1.0.3 Strings, Sprachen.- 1.1 Turing-Maschinen.- 1.1.1 Das allgemeine Modell.- 1.1.2 Verschiedene Speichertypen.- 1.1.3 Beispiele für die Arbeitsweise von TM.- 1.1.4 Berechenbarkeit.- 1.1.5 Nichtdeterministische Berechnungen.- 1.2 Das Rechnen mit TM.- 1.2.1 Elementare Techniken.- 1.2.2 Simulation, Band- und Kopf-Reduktion.- 1.2.3 Universelle Maschinen.- 1.3 Mathematische Grundlagen.- 1.3.1 Notation.- 1.3.2 Asymptotisches Wachstum.- 1.3.3 Wachstumsordnungen.- 1.3.4 Rekursionsgleichungen.- 1.4 Die Komplexität von TM.- 1.4.1 Schranken, Maße und Konstruierbarkeit.- 1.4.2 Komplexitätsklassen.- 1.4.3 Diagonalisierung.- 1.4.4 Bandkompression.- 1.4.5 Lineare Beschleunigung.- 1.5 Übungsaufgaben.- 1.6 Bemerkungen und Literaturhinweise.- 2 Weitere Maschinenmodelle.- 2.1 Registermaschinen.- 2.1.1 Das RAM-Modell.- 2.1.2 Komplexitätsmaße für RAMs.- 2.1.3 Simulation von RAMs durch TM.- 2.1.4 Simulation von TM durch RAMs.- 2.2 Schaltkreis-Familien.- 2.2.1 Boolesche Funktionen und Schaltkreise.- 2.2.2 Schaltkreiskomplexität.- 2.2.3 Uniformität.- 2.2.4 Simulation von Schaltkreisfamilien durch TM.- 2.2.5 Simulation von TM durch Schaltkreisfamilien.- 2.2.6 Universelle Schaltkreise.- 2.3 Arithmetische Modelle, Entscheidungsgraphen.- 2.3.1 Arithmetische RAMs und Schaltkreise.- 2.3.2 Entscheidungsbaum-Modelle.- 2.4 Übungsaufgaben.- 2.5 Bemerkungen und Literaturhinweise.- 3 Hierarchie-Sätze.- 3.1 Untere Schranken und Komplexitätslücken.- 3.1.1 Logarithmische Platzschranke.- 3.1.2 Quadratische Zeitschranke für 1-Band Maschinen.- 3.1.3 Komplexitätslücke bei zeitbeschränkten 1-Band TM.- 3.1.4 Komplexitätslücke bei kleinen Platzschranken.- 3.2 Deterministische Hierarchien.- 3.2.1 Allgemeiner Hierarchiesatz.- 3.2.2 Zeithierarchien.- 3.2.3 Platzhierarchien.- 3.3 Translation.- 3.4 Nichtdeterministische Hierarchien.- 3.4.1 Komplementabschluß von nichtdeterministischem Platz.- 3.4.2 Nichtdeterministischer Platzhierarchiesatz.- 3.4.3 Nichtdeterministischer Zeithierarchiesatz.- 3.5 Das Komplexitätsmaß Reversal.- 3.5.1 Reversalbeschränkte TM.- 3.5.2 Vergleich von Time und Reversal.- 3.5.3 Vergleich von Space und Reversal.- 3.5.4 Bandreduktion und Reversal für NTM.- 3.6 Abstrakte Komplexitätstheorie.- 3.6.1 Allgemeines Gap-Theorem.- 3.6.2 Speedup-Theorem.- 3.6.3 Union-Theorem.- 3.6.4 Abstrakte Komplexitätsmaße.- 3.7 Übungsaufgaben.- 3.8 Bemerkungen und Literaturhinweise.- 4 Vergleich von Speicherstrukturen.- 4.1 Ein allgemeines Speichermodell.- 4.1.1 On-line versus off-line.- 4.1.2 Konstruierbare Speicher.- 4.1.3 Lineare Bandsimulation konstruierbarer Speicher.- 4.2 1-dimensionale Speicher.- 4.2.1 Bandreduktion für NTM.- 4.2.2 Simulation von Mehrkopf-Maschinen.- 4.2.3 TM mit separatem Einweg-Eingabeband.- 4.2.4 1 versus 2 Bänder bei Zweiweg-Eingabe.- 4.3 Untere Schranken für Speicherzugriffe.- 4.3.1 Kolmogorov-Komplexität von Strings.- 4.3.2 Der Einfluß des Radius.- 4.4 Obere Schranken für Speicherzugriffe.- 4.4.1 Einbettung von Graphen.- 4.4.2 Kompaktifizierung.- 4.4.3 Schnelle Simulationen.- 4.5 Übungsaufgaben.- 4.6 Bemerkungen und Literaturhinweise.- 5 Zeit- versus Platzkomplexität.- 5.1 Time-Space-Relationen für 1-Band TM.- 5.1.1 Simulation platzbeschränkter 1-Band DTM.- 5.1.2 Simulation platzbeschränkter 1-Band NTM.- 5.1.3 Mehrdimensionale 1-Band TM.- 5.2 Das Pebble-Game.- 5.2.1 Berechnungsgraphen.- 5.2.2 Superkonzentratoren.- 5.2.3 Schichtungen von Graphen.- 5.3 Platzeffiziente Simulation von TM und RAMs.- 5.3.1 Lineare Speicher.- 5.3.2 Nichtlineare Speicher.- 5.3.3 Auxiliary Pushdown TM.- 5.4 Simultane Ressource-Schranken.- 5.4.1 Schaltkreisweite.- 5.4.2 Vergleich der Ressourcen von TM und Schaltkreisen.- 5.5 Übungsaufgaben.- 5.6 Bemerkungen und Literaturhinweise.- 6 Sequentielle Komplexitätsklassen.- 6.1 Einführung.- 6.1.1 Notation.- 6.1.2 Zeit-Platz-Hierarchie.- 6.1.3 Reduzierbarkeit, Vollständigkeit.- 6.2 Die Klassen von L bis P.- 6.2.1 Labyrinth-Probleme zur Charakterisierung von L und NL.- 6.2.2 P -vollständige Probleme.- 6.3 NP-vollständige Probleme.- 6.3.1 Das Erfüllbarkeitsproblem.- 6.3.2 Selbstreduzierbarkeit.- 6.3.3 Erfüllbarkeit für 3-CNF.- 6.3.4 Graphenprobleme: Cliquen, Kreise und Überdeckungen.- 6.3.5 Das Färbungsproblem für Graphen.- 6.3.6 Diskrete Optimierung.- 6.3.7 NP -Vollständigkeit im strengen Sinne.- 6.3.8 Obere Schranken und Parameterkomplexität.- 6.4 Von NP bis PSP ACE.- 6.4.1 Die Struktur von NP.- 6.4.2 Die Relation zwischen NP und co-NP.- 6.4.3 UP, Einweg-Funktionen und Kryptologie.- 6.4.4 PSP ACE -Vollständigkeit.- 6.5 Linguistische Klassifikationen.- 6.5.1 Formale Grammatiken.- 6.5.2 Die Chomsky-Hierarchie.- 6.5.3 Kontextfreie Sprachen und Log CFL.- 6.5.4 Reguläre Ausdrücke.- 6.6 Übungsaufgaben.- 6.7 Bemerkungen und Literaturhinweise.- Stichwortverzeichnis.- Symbolverzeichnis.- Zeitschriftenverzeichnis.- Konferenzverzeichnis.- Verzeichnis von Fachorganisationen.
£38.69
Springer Fachmedien Wiesbaden Algorithmen: Vom Problem zum Programm
Book SynopsisDieser Band behandelt numerische Algorithmen, die in der traditionellen Schulmathematik eine wichtige Rolle spielen. Ziel ist es dabei, nicht nur die einzelnen Algorithmen kennenzulernen, sondern zugleich auch die Methodik, die zur Elementarisierung mathematischer Probleme und zur Lösung in endlich vielen Schritten führt. Darüber hinaus werden nichtnumerische Such-, Sortier- und Simulationsalgorithmen dargestellt, die sich in der Schule in spielerischer und kreativer Weise behandeln lassen. Für die konkreten Lösungen einer mathematischen Aufgabe ist immer ein Algorithmus erforderlich. Vom Euklidischen Algorithmus zur Ermittlung des größten gemeinsamen Teilers zweier natürlicher Zahlen bis zur Lösung linearer Gleichungssysteme mit dem Gaußschen Algorithmus sind Algorithmen unverzichtbar. Die zweite, durchgesehene und erweiterte Auflage dieses Hochschullehrbuches enthält zusätzliche Beispiele, Lösungen und Aufgaben.Table of Contents1 Einführung.- 1.1 Was ist ein Algorithmus?.- 1.2 Zielsetzung.- 1.3 Beispiel 1 Potenzierung.- 1.4 Beispiel 2 Russisches Roulette.- 1.5 Folgerungen und Ausblick.- 2 Numerische Algorithmen.- 2.1 Teilbarkeitslehre in N.- 2.1.1 Teilbarkeit und Teilermengen.- 2.1.2 Größter gemeinsamer Teiler und kleinstes gemeinsames Vielfaches.- 2.1.3 Primzahleigenschaft.- 2.1.4 Primzahltabelle von 2 bis n.- 2.1.5 Zerlegung einer natürlichen Zahl in Primfaktoren.- 2.2 Stellenwertsysteme in Q.- 2.2.1 Darstellung natürlicher Zahlen in Stellenwertsystemen.- 2.2.2 Darstellung rationaler Zahlen in Stellenwertsystemen.- 2.2.3 Teilbarkeit und Teilbarkeitskriterien.- 2.3 Iterationen in Q.- 2.3.1 Quadratwurzeliteration (Halbierungsverfahren).- 2.3.2 Nullstellenbestimmung.- 2.3.3 Nullstelle einer kubischen Gleichung.- 2.3.4 Quadratwurzelnäherung nach Newton-Heron.- 3 Nichtnumerische Algorithmen.- 3.1 Suchvorgänge.- 3.1.1 Suchen eines Elementes in einer geordneten Liste.- 3.1.2 Einordnen eines Elementes in eine geordnete Liste.- 3.1.3 Zweidimensionales Suchen (Kobold).- 3.1.4 Damen-Problem.- 3.2 Sortiervorgänge.- 3.2.1 Minimales Element einer Liste.- 3.2.2 Sortieren einer Liste von n Wörtern mit der Austauschmethode.- 3.2.3 Sortieren einer Liste von n Wörtern mit der Sprudelmethode.- 3.2.4 Sortieren einer Liste von n Wörtern mit Quicksort.- 3.2.5 Sortieren durch Mischen.- 3.2.6 Türme von HANOI.- 4 Anhang: Arbeiten mit Visual-BASIC.- 4.1 EXCEL-Tabelle und Programm-Modul(e).- 4.2 EXCEL-Tabelle mit variabler Ein- und Ausgabe.- Literaturhinweise.- Stichwortverzeichnis.
£18.99
Wiley-VCH Verlag GmbH Machine Vision Algorithms and Applications
Book SynopsisThe second edition of this successful machine vision textbook is completely updated, revised and expanded by 35% to reflect the developments of recent years in the fields of image acquisition, machine vision algorithms and applications. The new content includes, but is not limited to, a discussion of new camera and image acquisition interfaces, 3D sensors and technologies, 3D reconstruction, 3D object recognition and state-of-the-art classification algorithms. The authors retain their balanced approach with sufficient coverage of the theory and a strong focus on applications. All examples are based on the latest version of the machine vision software HALCON 13.Table of ContentsINTRODUCTION IMAGE ACQUISITION Illumination Lenses Cameras Camera-Computer Interfaces MACHINE VISION ALGORITHMS Fundamental Data Structures Image Enhancement Geometric Transformations Image Segmentation Feature Extraction Morphology Edge Extraction Segmentation and Fitting of Geometric Primitives Camera Calibration Stereo Reconstruction Template Matching Optical Character Recognition MACHINE VISION APPLICATIONS Wafer Dicing Reading of Serial Numbers Inspection of Saw Blades Print Inspection Inspection of Ball Grid Arrays Surface Inspection Measuring of Spark Plugs Molding Flash Detection Inspection of Punched Sheets 3D Plane Reconstruction with Stereo Pose Verification and Resistors Classification of Non-Woven Fabrics
£53.55
Wiley-VCH Verlag GmbH Maschinelles Lernen mit Python und R für Dummies
Book SynopsisMaschinelles Lernen ist aufregend: Mit schnellen Prozessoren und großen Speichern können Computer aus Erfahrungen lernen, künstliche Intelligenz kommt wieder in Reichweite. Mit diesem Buch verstehen Sie, was maschinelles Lernen bedeutet, für welche Probleme es sich eignet, welche neuen Herangehensweisen damit möglich sind und wie Sie mit Python, R und speziellen Werkzeugen maschinelles Lernen implementieren. Sie brauchen dafür keine jahrelange Erfahrung als Programmierer und kein Mathematikstudium. Die praktische Anwendung maschinellen Lernens steht in diesem Buch im Vordergrund. Spielen Sie mit den Tools und haben Sie Spaß dabei! Lernen Sie Fakten und Mythen zum maschinellen Lernen zu unterscheiden.Table of ContentsÜber die Autoren 13 Einführung 25 Teil I: Einführung in das maschinelle Lernen 29 Kapitel 1: Künstliche Intelligenz in Fiktion und Realität 31 Kapitel 2: Lernen im Zeitalter von Big Data 43 Kapitel 3: Ein Ausblick auf die Zukunft 53 Teil II: Einrichtung Ihrer Programmierumgebung 63 Kapitel 4: Installation einer R-Distribution 65 Kapitel 5: Programmierung mit R und RStudio 83 Kapitel 6: Installation einer Python-Distribution 107 Kapitel 7: Programmierung mit Python und Anaconda 127 Kapitel 8: Weitere Softwareprogramme für maschinelles Lernen 151 Teil III: Mathematische Grundlagen 159 Kapitel 9: Mathematische Grundlagen des maschinellen Lernens 161 Kapitel 10: Fehlerfunktionen und ihre Minimierung 179 Kapitel 11: Validierung von maschinellem Lernen 191 Kapitel 12: Einfache Lerner 209 Teil IV: Aufbereitung und Verwendung von Daten zum Lernen 225 Kapitel 13: Vorverarbeitung von Daten 227 Kapitel 14: Ausnutzung von Ähnlichkeiten in Daten 245 Kapitel 15: Einfache Anwendung von linearen Modellen 265 Kapitel 16: Komplexere Lernverfahren und neuronale Netze 287 Kapitel 17: Support Vector Machines und Kernel-Funktionen 303 Kapitel 18: Kombination von Lernalgorithmen in Ensembles 321 Teil V: Praktische Anwendung von maschinellem Lernen 337 Kapitel 19: Klassifikation von Bildern 339 Kapitel 20: Bewertung von Meinungen und Stimmungslagen 353 Kapitel 21: Produkt- und Filmempfehlungen 373 Teil VI: Der Top-Ten-Teil 387 Kapitel 22: Zehn wichtige Pakete für maschinelles Lernen 389 Kapitel 23: Zehn Methoden zur Verbesserung Ihrer maschinellen Lernmodelle 395 Stichwortverzeichnis 403
£23.70
Wiley-VCH Verlag GmbH Algorithmen und Datenstrukturen für Dummies
Book SynopsisDieses Buch führt Sie sachte in die Denkweisen des Fachs "Algorithmen und Datenstrukturen" ein. Es erklärt Informatik-Anfängern Terminologie, Notation und zentrale Inhalte des Fachgebiets auf anschauliche und sehr unterhaltsame Weise. Ein Fokus sind die Techniken und Tricks, die Sie brauchen, um effiziente Algorithmen und Datenstrukturen zu bauen. Sie werden auch in die Lage versetzt, Pseudocode in der typischen akademischen Darstellung zu verstehen und in unterschiedlichen Programmiersprachen zu realisieren oder umgekehrt grundlegende algorithmische Ideen als Pseudocode zu dokumentieren.Table of ContentsEinleitung 17 Über dieses Buch 17 Törichte Annahmen über den Leser 19 Wie dieses Buch aufgebaut ist 19 Symbole, die in diesem Buch verwendet werden 20 Wie es weitergeht 21 Teil I Grundbegriffe 23 Kapitel 1 Algorithmen 25 Das sind Algorithmen 25 Algorithmen lösen Probleme 26 Algorithmen basieren auf einem einfachen Maschinenmodell 30 Algorithmen sind bewertbar 32 Algorithmen agieren in Modellwelten 32 Algorithmen sind keine Programme 33 Algorithmen klar beschreiben 35 Sprechen Sie Pseudocode? 35 Mathematische Ausdrücke sind erlaubt 37 Algorithmen sprechen sogar Deutsch 37 Algorithmen sind Lösungen, keine Probleme 38 Algorithmen haben zählbare Schritte 39 Algorithmen sollten korrekt sein 40 Algorithmen können sich aufhängen 41 Das Halteproblem ist unlösbar 42 Algorithmen richtig verstehen 43 Kapitel 2 Qualität von Algorithmen 47 So gut sind Algorithmen 47 Wer ist der Leichteste? 48 Laufzeiten vergleichen 50 Laufzeitanalysen 53 Lineare Laufzeiten 53 Oh du großes O! 55 Arten der Laufzeitanalyse 57 Laufzeiten konkret bestimmen 59 Faustregel 1: Bei Schleifen muss man multiplizieren 59 Faustregel 2: Der stärkste Summand dominiert 61 Vorsicht vor versteckten Kosten 61 Randomisierte Laufzeitanalyse 62 Das Auswahlproblem 63 QuickSelect: Ein randomisierter Algorithmus 63 Amortisierte Laufzeitanalyse 66 Ein Binärzähler an der Fassade 66 Ein sparsamer Stapel 69 Die Potenzialmethode 71 Kapitel 3 Daten und ihre Struktur 75 Aus Daten Strukturen bauen 75 Datenstrukturen: die Essenz 76 Datenstrukturen im Pseudocode 78 Algebraische Datentypen 92 Funktion folgt Struktur 97 Endrekursive und linear-rekursive Funktionen 98 Linear-rekursive Funktionen und die Akkumulatortechnik 101 Strukturelle Rekursion 103 Teilen und Herrschen 105 Strukturen durchlaufen: Iteratoren und Traversierungen 106 Teil II Algorithmen in Den Gärten Der Strukturen 111 Kapitel 4 Listen: Immer einer nach dem anderen 113 Listen: Datenmodell und Implementierung 116 Datenabstraktion: Was Listen so können sollen 118 Alles ist ewig und Rekursion ist gut 129 Listen in Funktionalistan 131 Persistente Datenstrukturen 143 Ordnung herstellen: imperativ und funktional 145 Nicht alles ist ewig und Form ist nicht Inhalt 152 Warteschlange als funktionale Datenabstraktion 152 Warteschlangen mit Amortisation 155 Rückblick: Imperative und funktionale Algorithmen 157 Kapitel 5 Bäume: Immer einer über dem anderen 161 Wo ist die Kokosnuss? 162 Baumtraversierungen 163 Mit Stapeln in die Tiefe tauchen 168 Mit Warteschlangen in die Breite gehen 173 Die Kleinen nach links, die Großen nach rechts 176 Binäre Suchbäume 177 Verzeichnisse als Suchbäume 179 Bäume verkleiden sich gerne mal 181 Tries 182 Prioritätswarteschlangen 184 Bäume als Datenmodell 189 Ausdrucksbäume 190 Mit Stapeln übersetzen und auswerten 191 Kapitel 6 Graphen: Jeder mit jedem 195 Im Irrgarten der sozialen Netzwerke 196 Ein kurzer Blick in die Welt der Graphen 198 Einflussnahme als Graphenproblem 202 Graphen traversieren 203 Datenstrukturen für Graphen 206 Nachbarschaften dokumentieren 207 Daten und Probleme machen Graphen 210 Was nicht passt, wird passend gemacht 212 Erst die Schuhe, dann das Hemd – oder wie? 214 Topologische Sortierung, ein guter Start in den Tag 214 Liste folgt Funktional 216 Array folgt Imperativ 217 Teil III Probleme Und Ihre Lösungen 221 Kapitel 7 Sortieren 223 Alles in Ordnung 223 Das Sortierproblem 224 SelectionSort: So lange wählen, bis es passt 227 Laufzeit von SelectionSort 228 MergeSort: Geteiltes Leid ist halb sortiert 229 Sortierte Teilarrays verschmelzen mit Merge 230 Teilen und Herrschen 232 Laufzeit von MergeSort 232 QuickSort: Quick and Easy 234 Partition teilt das Array auf 234 Sortieren mit QuickSort 235 Worst-Case-Laufzeit von QuickSort 236 Randomisierung 237 HeapSort: Ein Haufen Arbeit 237 Die Datenstruktur Heap 238 Der Heap als Priority Queue 239 Besser sortieren mit dem Heap 240 Die maximale Sortiergeschwindigkeit 241 Sortieren in Linearzeit 244 CountingSort: Sortieren durch Zählen 244 Sortieren nach Ziffern 245 Stabile Sortierverfahren 247 RadixSort: Mehrfach ziffernweise sortieren 248 Weitere Sortieralgorithmen 249 BubbleSort: Nachbarn vertauschen 249 Gnomesort: Immer hin und her 250 InsertionSort: Spielkarten dazwischen schieben 251 Kapitel 8 Rucksack packen 253 Wie man einen Koffer packt 253 Das Rucksackproblem 253 Das Wichtigste zuerst einpacken 255 Alles ausprobieren 257 Suchen im Entscheidungsbaum 258 Den Suchraum begrenzen 261 Probleme langsam wachsen lassen 264 Wachsende Probleme klug speichern 267 Sich dem Optimum annähern 270 Lineare Optimierung 274 Optimierung von Produktionsmengen 274 Ein System von Ungleichungen 275 Ziel: Gewinnmaximierung 275 Ganzzahlige lineare Optimierung 276 Das Rucksackproblem als ILP 277 Kapitel 9 Mengen und ihre Speicherung 279 Ich bin eine Menge 281 Imperative Datenabstraktion für Mengen 283 Funktionale Datenabstraktion für Mengen 285 Gut gehackt ist schnell gefunden 290 Hashfunktionen 292 Hashtabellen 293 Garantiert gut gehackt 298 Derselbe ist nicht immer der Gleiche 300 Viel ist oft eine Menge 304 Wer Ordnung hält, ist nur zu faul zum Suchen 306 Bäume balancieren 308 Rot-Schwarz-Bäume 311 Kapitel 10 Verbindungen finden 321 Kürzeste Pfade 322 Alle kürzesten Pfade von einem Start aus 322 Vom Vertrauten ins Unbekannte 325 Kürzester Pfad zu allen Knoten 328 Dijkstras Algorithmus 330 Datenstrukturen für Dijkstras Algorithmus 333 Verbundenes aufspüren 334 Verbundene Komponenten identifizieren 335 Datenstrukturen bei der Berechnung verbundener Komponenten 338 Disjunkte Mengen als Datenstruktur 340 Laufzeiten 344 Spann mir einen Graphen auf 345 Minimaler Spannbaum 346 Kruskals Algorithmus 347 Teil IV Algorithmische Techniken 351 Kapitel 11 Probleme totschlagen 353 Erschöpfende Suche 354 Die üblichen Verdächtigen: Kombinatorische Objekte 355 Konzentrierte oder weit ausschweifende Suche 358 Die erschöpfende Suche nach acht friedlichen Damen 362 Iterative und rekursive Erzeugung des Suchraums 364 Schleifen rekursiv erzeugen 364 Einen baumartigen Suchraum rekursiv erzeugen 366 Backtracking 369 Kandidaten nicht stückweise bewertbar: kein Backtracking 371 Backtracking als Suche im Zustandsraum 373 Verzweigen und Begrenzen 375 Erschöpfende und Backtracking-Suche im Irrgarten 375 Optimierungen und Bewertungsfunktionen 377 Komplexitätsklassen: Schwere Probleme führen zu anstrengender Arbeit 380 Schwer ist, was den Besten schwerfällt 380 Ein Labyrinth der Kameras 382 Das nichtdeterministische Orakel 383 Schwer, schwerer, NP-schwer 385 Wie man mit schweren Problemen umgeht 387 NP-schwer ≠ hoffnungslos 387 Gute Ideen sind kein Hexenwerk 390 Kapitel 12 Teilen und Herrschen 393 Aufgaben auf Mitarbeiter abwälzen 393 Das Einwohnermeldeamt von Bürokrazien 393 Das Prinzip Teilen und Herrschen 395 Laufzeiten bei Teilen und Herrschen 396 Das Mastertheorem 397 Fall 1: Der Chef arbeitet mehr 398 Fall 2: Der Chef arbeitet gleich viel 399 Fall 3: Der Chef arbeitet weniger 400 Gibt es noch weitere Fälle? 401 So bestimmt man, welcher Fall vorliegt 401 Binärsuche 403 Der Suchbaum in einfach 403 Grenzen des Suchbereichs 405 Weitere Beispiele für Teilen und Herrschen 407 Sortieren 407 Matrizen multiplizieren 408 Minimaler Punktabstand 409 Kapitel 13 Dynamisches Programmieren 411 Ein profitabler Bauauftrag 411 Das Maximale-Teilsumme-Problem 412 Gier hilft nicht 412 Rohe Gewalt hilft eher 413 Inkrementelle Gewalt ist weniger roh 413 Ein Stück abschneiden und Herrschen 414 Zwischenergebnisse merken 416 Den Algorithmus vom Kopf auf die Füße stellen 418 Der ultimative Maximale-Teilsumme-Algorithmus 418 Probleme wachsen lassen 419 Das Prinzip des dynamischen Programmierens 419 Beispiel 1: Minimum 420 Beispiel 2: Fibonacci-Zahlen 421 Beispiel 3: Rucksack packen 424 Vergleich von Texten 424 Die Editierdistanz 425 Strings alignieren 426 Arbeitsteilung auf der Alignmentbaustelle 427 Optimale Alignments mit dynamischem Programmieren 428 Der Weg zum Optimum 431 Entscheidungen merken 431 Den Pfad zurückfinden 433 Kapitel 14 Näherungslösungen 437 Heuristiken 437 Interpolationssuche 438 Heuristisches Verzweigen und Begrenzen 441 Der A*-Algorithmus 443 Approximation 446 TSP: Die kürzeste Rundreise 446 Gierige Heuristik 447 Lokale Suche 449 Approximation ohne Heuristik 450 Gier 453 Das Wechselgeldproblem 455 Das Problem der Mengenüberdeckung 458 Gier in Perfektion 461 Huffman-Codierung 461 Teil V Der Top-Ten-Teil 465 Kapitel 15 Zehn Datenabstraktionen und Datenstrukturen 467 Stapel 468 Warteschlange 469 Prioritätswarteschlange 469 Liste 470 Array 471 Menge 471 Verzeichnis 472 Relation 472 Graph 473 Baum 474 Kapitel 16 Zehn Ratschläge, wenn (bevor) der kleine Frust kommt 475 Rekursion ist deine Freundin 475 Mathematik ist einfach 476 Pseudocode ist verstehbar 477 Abstraktion ist gut 477 Sei auch mal funktional 478 Ein Bild sagt mehr als 1000 Worte 478 Vieles ist solides Handwerk 479 Es geht auch um Kreativität 479 Unterscheide Datenmodell und Datenstruktur 480 Was schwierig aussieht, ist oft auch schwierig 480 Stichwortverzeichnis 481
£21.38
Wiley-VCH Verlag GmbH Allgemeinbildung Digitalisierung für Dummies
Book Synopsis"Die Digitalisierung geht nicht mehr weg." - Ein grundlegendes Verständnis der Prinzipien der Digitalisierung und ihrer wichtigsten Anwendungen ist deshalb die Voraussetzung, um im Beruf und als Privatperson informierte Entscheidungen treffen zu können - ob es nun um Kryptowährungen, New Work oder den Schutz der eigenen Daten in sozialen Medien geht. In diesem Buch wird das Thema Digitalisierung anschaulich und unterhaltsam aufbereitet. Der Fokus liegt auf der fundierten und leicht verdaulichen Vermittlung der Grundlagen, die es Ihnen ermöglicht, nach der Lektüre eigenständig auf dem Laufenden zu bleiben und neue Entwicklungen mit ihren Konsequenzen zu verstehen und einzuordnen.Trade Review"... Wer sich in den verschiedenen Bereichen der Digitalisierung fit machen möchte, dem sei der Ratgeber ?Allgemeinbildung Digitalisierung für Dummies? empfohlen. (Hab mehr vom Leben; im Juli 2022)Table of ContentsÜber die Autorin 9 Einführung 19 Törichte Annahmen über die Leser 20 Wie dieses Buch aufgebaut ist 20 Teil I: Was heißt Digitalisierung? 20 Teil II: Daten und Algorithmen – die Welt als Einsen und Nullen 20 Teil III: Digitalisierung zum Anfassen – Schnittstellen zur physischen Realität 21 Teil IV: Digitalisierung in Aktion – Anwendungsbereiche 21 Teil V: Digitalisierung und wir – gesellschaftliche Auswirkungen 21 Teil VI: Der Top-Ten- Teil 22 Symbole, die in diesem Buch verwendet werden 22 Wie es weitergeht 22 Teil I: Was heißt Digitalisierung? 23 Kapitel 1: Digitale Welt – was bringt uns das? 25 Die reale Welt in Zahlen abbilden 27 Digitale Abbilder sind unvollständig 28 … dürfen es aber auch sein 29 Informationen (fast) umsonst übermitteln und vervielfältigen 30 Informationen intelligent verarbeiten 30 Teil II: Daten und Algorithmen – die Welt als Einsen und Nullen 33 Kapitel 2: Wo wohnt Information? 35 Information existiert nur auf einem Träger 36 Hebel, Walzen, Rechenschieber 36 Mechanische Träger sind groß und langsam 40 Vom Rauchzeichen zum Telegrafen 40 Eine gute Idee: Das Relais 41 Logisch: 1 ist NICHT 0 43 Ein Saal voller Flipflops 45 Hier können Sie Ihre Bits registrieren 47 Daten auf der Flucht 50 Ein Netzwerk für (fast) alles: Das Internet 52 Vom Internet zum World Wide Web 58 Kapitel 3:Algorithmen: Mit Daten Dinge tun 59 Kochrezepte für den Computer 60 Englisch: Weltsprache auch für Computer 62 In kleinen Schritten zum Erfolg 65 Das Problem kenne ich irgendwoher … 66 Große Datenmengen: Mehr ist manchmal einfach mehr 67 So lernen Maschinen 73 Supervised Learning: Die Maschine an die Hand nehmen 75 kNN-Algorithmus: In guter Nachbarschaft 76 Unsupervised Learning: Auf sich allein gestellt 79 k-Means Clustering: Ballungsräume finden 80 Das Hirn nachbauen: Künstliche neuronale Netze 82 Das neuronale Netz in Aktion 86 Schicht um Schicht: Deep Learning 87 Starke und schwache künstliche Intelligenz 87 Meine Geheimnisse gehören mir: Kryptografie 90 Die Blockchain: Revolution oder Betrugsmasche? 92 Unkopierbares Geld 94 Betrug ist teuer 96 Mining: So wird Geld gemacht 99 Nützlicher als Bitcoin 99 Automatisierung mit Smart Contracts 102 Blockchain ohne Geld 106 Kapitel 4: Computer mal anders: Quanten, DNA und andere 109 Ternäre Logik: Flip, Flap, Flop 109 Biologische Computer 110 Quantencomputer und die spukhafte Fernwirkung 113 Die Antwort ist 42: Deep Thought 116 Teil III: Digitalisierung zum Anfassen – Schnittstellen zur physischen Realität 119 Kapitel 5: Virtual und Augmented Reality 121 Virtuelle Realität: Eine Dimension mehr 123 Vom Pixel zum Voxel 123 3D-Modellierung und –Rendering 125 Räumlich sehen, ohne VR-krank zu werden 128 Augmented Reality: Die bessere Realität 130 Kapitel 6: Internet of Things und Industrie 4.0 137 Sensoren und Aktoren: Wir regeln das 138 Kybernetik: Alles ist ein System 139 Das hilfreiche Zuhause 140 Cyber-Physical Systems: Maschinen im Internet 143 Kapitel 7: Robotik 145 Wie sehe ich aus? Design eines Roboters 149 Die Gesetze der Robotik 151 Kapitel 8: Nanotechnologie 155 Viel Spielraum nach unten 155 Maschinen auf Kohlenstoffbasis 158 Teil IV: Digitalisierung in Aktion – Anwendungsbereiche 161 Kapitel 9: Soziale Medien und Netzwerke 163 Smileys, Emoticons, Emojis 164 Die Geburt des Blogs 167 Vom Onlinetagebuch zum (We)Blog 168 Der Aufstieg von Facebook 169 Feeds, Likes und Dopamin 171 Nichts verpassen: Soziale Netzwerke unterwegs 172 Alte und neue soziale Netzwerke 173 Triff mich im Livestream 173 Werbung in sozialen Netzwerken 176 Soziale Netzwerke und Datenschutz 177 Dezentrale Netzwerke 179 Kapitel 10: Digitales Arbeiten und New Work 183 Homeoffice und mobiles Arbeiten 183 Digitale Nomaden 186 New Work oder gar kein Work? 186 Decentralized Autonomous Organizations (DAOs) 188 Geld, kontrolliert von Algorithmen 189 Kapitel 11: E-Commerce, digitale Zahlungsmittel und Kryptowährungen 191 Der Siegeszug von Amazon und eBay 192 PayPal und die Kontensperrung 194 Kryptowährungen: Ohne Netz und doppelten Boden 194 Micropayments: Kleinvieh macht mehr Mist 197 Kapitel 12: Digitale Gesundheit 203 Wertvolles Gut: Gesundheitsdaten 203 Telematikinfrastruktur 206 Quantified Self: Wer bin ich – und wie kann ich das messen? 210 Wir sind Cyborgs 212 Schluss mit Wartezimmern? 214 Kapitel 13: Smarte Mobilität und autonomes Fahren 217 Wissen, wo es langgeht 217 Autonome Automobile 220 Teil V: Digitalisierung und wir – gesellschaftliche Auswirkungen 227 Kapitel 14: Informationelle Selbstbestimmung und Überwachung 229 Vom Volkszählungsgesetz zur Verfassungsbeschwerde 230 Bürger unter Beobachtung 231 Post Privacy: Nichts zu verbergen? 232 Bitte vergiss mich 233 Kapitel 15: Nudging und Bevormundung 235 Nicht schubsen! 235 Unter uns Denkfaulen 237 Lieber nichts verlieren als etwas gewinnen 238 Soziale Einflüsse und Normen 238 Falsche Einschätzung von Wahrscheinlichkeiten 239 So geht Nudging 240 Kapitel 16: Digitale Bohème und digitales Prekariat 243 Selbst und ständig 243 Der Mensch als Automat 245 Selbstkontrolle, Selbstökonomisierung, Selbstrationalisierung 246 Kapitel 17: Informationsflut und ständige Erreichbarkeit 249 Ein Online-Brain für die digitale Welt 250 Nie wieder Langeweile? 251 Langeweile macht kreativ 252 Transaktionsgedächtnis: Wissen, wo was steht 253 Ihr Smartphone: Risiken und Nebenwirkungen 254 Kapitel 18: Digitale Helfer und Verlust zwischenmenschlicher Kontakte 257 Teil VI: Der Top-Ten- Teil. 261 Kapitel 19: Zehn hörenswerte Vorträge zur Digitalisierung 263 Hirne hacken: Menschliche Faktoren in der IT-Sicherheit 264 Ich sehe, also bin ich … Du 264 Embracing Post Privacy 265 Bias in Algorithmen 265 Digitale Entmündigung 266 Hold Steering Wheel! Autopilots and Autonomous Driving 266 Quantum Computing: Are we there yet? 266 Virtual Reality für Arme 267 Computer, Kunst und Kuriositäten 267 What the cyberoptimists got wrong – and what to do about it 268 Abbildungsverzeichnis 269 Stichwortverzeichnis 273
£12.99
Springer Fachmedien Wiesbaden Algebraische Algorithmen
Book SynopsisThemen sind die grundlegenden arithmetischen und algebraischen Objekte: ganze Zahlen, endliche Körper, euklidische Ringe und Polynomringe. Es behandelt Algorithmen für Primzahltests, Faktorisierungsmethoden für ganze Zahlen und Polynome sowie Verfahren zur Berechnung von Gröbner Basen. Besondere Aufmerksamkeit wird der Darstellung der behandelten Objekte, der Analyse der Algorithmen und der Lösung diophantischer Gleichungen und Gleichungssysteme gewidmet.Trade Review"Sehr empfehlenswert für Studierende, Lehrer und mathematisch interessierte Schüler." (ekz- Informationsdienst, 31/99)Table of ContentsEinleitung - Euklidische Ringe und Ringe mit eindeutiger Primfaktorzerlegung - Ring der ganzen Zahlen - Restklassenringe, Primzahltests und Faktorisierung in Z - Körper der rationalen und reellen Zahlen - Polynomringe - Polynomfaktorisierung - Polynomideale
£26.59
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG How to Solve It: Modern Heuristics
Book SynopsisNo pleasure lasts long unless there is variety in it. Publilius Syrus, Moral Sayings We've been very fortunate to receive fantastic feedback from our readers during the last four years, since the first edition of How to Solve It: Modern Heuristics was published in 1999. It's heartening to know that so many people appreciated the book and, even more importantly, were using the book to help them solve their problems. One professor, who published a review of the book, said that his students had given the best course reviews he'd seen in 15 years when using our text. There can be hardly any better praise, except to add that one of the book reviews published in a SIAM journal received the best review award as well. We greatly appreciate your kind words and personal comments that you sent, including the few cases where you found some typographical or other errors. Thank you all for this wonderful support.Table of ContentsI What Are the Ages of My Three Sons?.- 1 Why Are Some Problems Difficult to Solve?.- II How Important Is a Model?.- 2 Basic Concepts.- III What Are the Prices in 7–11?.- 3 Traditional Methods — Part 1.- IV What Are the Numbers?.- 4 Traditional Methods — Part 2.- V What’s the Color of the Bear?.- 5 Escaping Local Optima.- VI How Good Is Your Intuition?.- 6 An Evolutionary Approach.- VII One of These Things Is Not Like the Others.- 7 Designing Evolutionary Algorithms.- VIII What Is the Shortest Way?.- 8 The Traveling Salesman Problem.- IX Who Owns the Zebra?.- 9 Constraint-Handling Techniques.- X Can You Tune to the Problem?.- 10 Tuning the Algorithm to the Problem.- XI Can You Mate in Two Moves?.- 11 Time-Varying Environments and Noise.- XII Day of the Week of January 1st.- 12 Neural Networks.- XIII What Was the Length of the Rope?.- 13 Fuzzy Systems.- XIV Everything Depends on Something Else.- 14 Coevolutionary Systems.- XV Who’s Taller?.- 15 Multicriteria Decision-Making.- XVI Do You Like Simple Solutions?.- 16 Hybrid Systems.- 17 Summary.- Appendix A: Probability and Statistics.- A.1 Basic concepts of probability.- A.2 Random variables.- A.2.1 Discrete random variables.- A.2.2 Continuous random variables.- A.3 Descriptive statistics of random variables.- A.4 Limit theorems and inequalities.- A.5 Adding random variables.- A.6 Generating random numbers on a computer.- A.7 Estimation.- A.8 Statistical hypothesis testing.- A.9 Linear regression.- A.10 Summary.- Appendix B: Problems and Projects.- B.1 Trying some practical problems.- B.2 Reporting computational experiments with heuristic methods.- References.
£71.24
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG LATIN 2006: Theoretical Informatics: 7th Latin
Book SynopsisThis book constitutes the refereed proceedings of the 7th International Symposium, Latin American Theoretical Informatics, LATIN 2006, held in March 2006. The 66 revised full papers presented together with seven invited papers were carefully reviewed and selected from 224 submissions. The papers presented are devoted to a broad range of topics in theoretical computer science with a focus on algorithmics and computations related to discrete mathematics as well as on cryptography, data compression and Web applications.Table of ContentsKeynotes.- Algorithmic Challenges in Web Search Engines.- RNA Molecules: Glimpses Through an Algorithmic Lens.- Squares.- Matching Based Augmentations for Approximating Connectivity Problems.- Modelling Errors and Recovery for Communication.- Lossless Data Compression Via Error Correction.- The Power and Weakness of Randomness in Computation.- Regular Contributions.- A New GCD Algorithm for Quadratic Number Rings with Unique Factorization.- On Clusters in Markov Chains.- An Architecture for Provably Secure Computation.- Scoring Matrices That Induce Metrics on Sequences.- Data Structures for Halfplane Proximity Queries and Incremental Voronoi Diagrams.- The Complexity of Diffuse Reflections in a Simple Polygon.- Counting Proportions of Sets: Expressive Power with Almost Order.- Efficient Approximate Dictionary Look-Up for Long Words over Small Alphabets.- Relations Among Notions of Security for Identity Based Encryption Schemes.- Optimally Adaptive Integration of Univariate Lipschitz Functions.- Classical Computability and Fuzzy Turing Machines.- An Optimal Algorithm for the Continuous/Discrete Weighted 2-Center Problem in Trees.- An Algorithm for a Generalized Maximum Subsequence Problem.- Random Bichromatic Matchings.- Eliminating Cycles in the Discrete Torus.- On Behalf of the Seller and Society: Bicriteria Mechanisms for Unit-Demand Auctions.- Pattern Matching Statistics on Correlated Sources.- Robust Model-Checking of Linear-Time Properties in Timed Automata.- The Computational Complexity of the Parallel Knock-Out Problem.- Reconfigurations in Graphs and Grids.- -Varieties, Actions and Wreath Product.- Local Construction of Planar Spanners in Unit Disk Graphs with Irregular Transmission Ranges.- An Efficient Approximation Algorithm for Point Pattern Matching Under Noise.- Oblivious Medians Via Online Bidding.- Efficient Computation of the Relative Entropy of Probabilistic Automata.- A Parallel Algorithm for Finding All Successive Minimal Maximum Subsequences.- De Dictionariis Dynamicis Pauco Spatio Utentibus.- Customized Newspaper Broadcast: Data Broadcast with Dependencies.- On Minimum k-Modal Partitions of Permutations.- Two Birds with One Stone: The Best of Branchwidth and Treewidth with One Algorithm.- Maximizing Throughput in Queueing Networks with Limited Flexibility.- Network Flow Spanners.- Finding All Minimal Infrequent Multi-dimensional Intervals.- Cut Problems in Graphs with a Budget Constraint.- Lower Bounds for Clear Transmissions in Radio Networks.- Asynchronous Behavior of Double-Quiescent Elementary Cellular Automata.- Lower Bounds for Geometric Diameter Problems.- Connected Treewidth and Connected Graph Searching.- A Faster Algorithm for Finding Maximum Independent Sets in Sparse Graphs.- The Committee Decision Problem.- Common Deadline Lazy Bureaucrat Scheduling Revisited.- Approximate Sorting.- Stochastic Covering and Adaptivity.- Algorithms for Modular Counting of Roots of Multivariate Polynomials.- Hardness Amplification Via Space-Efficient Direct Products.- The Online Freeze-Tag Problem.- I/O-Efficient Algorithms on Near-Planar Graphs.- Minimal Split Completions of Graphs.- Design and Analysis of Online Batching Systems.- Competitive Analysis of Scheduling Algorithms for Aggregated Links.- A 4-Approximation Algorithm for Guarding 1.5-Dimensional Terrains.- On Sampling in Higher-Dimensional Peer-to-Peer Systems.- Mobile Agent Rendezvous in a Synchronous Torus.- Randomly Colouring Graphs with Girth Five and Large Maximum Degree.- Packing Dicycle Covers in Planar Graphs with No K 5–e Minor.- Sharp Estimates for the Main Parameters of the Euclid Algorithm.- Position-Restricted Substring Searching.- Rectilinear Approximation of a Set of Points in the Plane.- The Branch-Width of Circular-Arc Graphs.- Minimal Eulerian Circuit in a Labeled Digraph.- Speeding up Approximation Algorithms for NP-Hard Spanning Forest Problems by Multi-objective Optimization.- RISOTTO: Fast Extraction of Motifs with Mismatches.- Minimum Cost Source Location Problems with Flow Requirements.- Exponential Lower Bounds on the Space Complexity of OBDD-Based Graph Algorithms.- Constructions of Approximately Mutually Unbiased Bases.- Improved Exponential-Time Algorithms for Treewidth and Minimum Fill-In.
£116.31
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Data Science and Classification
Book SynopsisData Science and Classification provides new methodological developments in data analysis and classification. The broad and comprehensive coverage includes the measurement of similarity and dissimilarity, methods for classification and clustering, network and graph analyses, analysis of symbolic data, and web mining. Beyond structural and theoretical results, the book offers application advice for a variety of problems, in medicine, microarray analysis, social network structures, and music.Trade ReviewFrom the reviews: "This book is a collection of papers presented at the Tenth Conference of the International Federation of Classification Societies. The contributors are primarily statisticians and computer scientists … . The typesetting and page layout are well done, and the graphics are very clear. … The main market for this book would be libraries, and researchers wanting a record of recent advances in statistical learning." (Jeffrey D. Picka, Technometrics, Vol. 49 (3), August, 2007)Table of ContentsSimilarity and Dissimilarity.- A Tree-Based Similarity for Evaluating Concept Proximities in an Ontology.- Improved Fréchet Distance for Time Series.- Comparison of Distance Indices Between Partitions.- Design of Dissimilarity Measures: A New Dissimilarity Between Species Distribution Areas.- Dissimilarities for Web Usage Mining.- Properties and Performance of Shape Similarity Measures.- Classification and Clustering.- Hierarchical Clustering for Boxplot Variables.- Evaluation of Allocation Rules Under Some Cost Constraints.- Crisp Partitions Induced by a Fuzzy Set.- Empirical Comparison of a Monothetic Divisive Clustering Method with the Ward and the k-means Clustering Methods.- Model Selection for the Binary Latent Class Model: A Monte Carlo Simulation.- Finding Meaningful and Stable Clusters Using Local Cluster Analysis.- Comparing Optimal Individual and Collective Assessment Procedures.- Network and Graph Analysis.- Some Open Problem Sets for Generalized Blockmodeling.- Spectral Clustering and Multidimensional Scaling: A Unified View.- Analyzing the Structure of U.S. Patents Network.- Identifying and Classifying Social Groups: A Machine Learning Approach.- Analysis of Symbolic Data.- Multidimensional Scaling of Histogram Dissimilarities.- Dependence and Interdependence Analysis for Interval-Valued Variables.- A New Wasserstein Based Distance for the Hierarchical Clustering of Histogram Symbolic Data.- Symbolic Clustering of Large Datasets.- A Dynamic Clustering Method for Mixed Feature-Type Symbolic Data.- General Data Analysis Methods.- Iterated Boosting for Outlier Detection.- Sub-species of Homopus Areolatus? Biplots and Small Class Inference with Analysis of Distance.- Revised Boxplot Based Discretization as the Kernel of Automatic Interpretation of Classes Using Numerical Variables.- Data and Web Mining.- Comparison of Two Methods for Detecting and Correcting Systematic Error in High-throughput Screening Data.- kNN Versus SVM in the Collaborative Filtering Framework.- Mining Association Rules in Folksonomies.- Empirical Analysis of Attribute-Aware Recommendation Algorithms with Variable Synthetic Data.- Patterns of Associations in Finite Sets of Items.- Analysis of Music Data.- Generalized N-gram Measures for Melodic Similarity.- Evaluating Different Approaches to Measuring the Similarity of Melodies.- Using MCMC as a Stochastic Optimization Procedure for Musical Time Series.- Local Models in Register Classification by Timbre.- Gene and Microarray Analysis.- Improving the Performance of Principal Components for Classification of Gene Expression Data Through Feature Selection.- A New Efficient Method for Assessing Missing Nucleotides in DNA Sequences in the Framework of a Generic Evolutionary Model.- New Efficient Algorithm for Modeling Partial and Complete Gene Transfer Scenarios.
£123.49
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Fundamental Algorithms for Computer Graphics: NATO Advanced Study Institute directed by J.E. Bresenham, R.A. Earnshaw, M.L.V. Pitteway
Book SynopsisAlgorithms provide the basic foundation for all computational processes. This volume presents algorithms at the foundational level and also at the various levels between this level and the user application. Some of these algorithms are classical and have become well established in the field. This material is therefore a rich source of information and is still relevant and up to date. The basic primitives of computer graphics have remained unchanged: lines, circles, conics, curves and characters. This volume contains reference material in all these areas. The higher levelsof contouring and surface drawing are also well covered. Developments in hardware architectures have continued since the first printing, but the basic principles of hardware/software trade-offs remain valid. This reprint is being published as a Study Edition to make the material more accessible to students and researchers in the field of computer graphics andits applications. The continuing popularity of the original book demonstrates the value and timeliness of its contents.Table of ContentsSection 1. Line and Area Algorithms.- Invited Papers.- “Theoretical and Linguistic Methods for Describing Straight Lines”.- “Run Length Slice Algorithm for Incremental Lines”.- “The Relationship between Euclid’s Algorithm and Run-Length Encoding”.- “Antialiasing in Practice”.- Submitted Papers.- “An Application of Euclid’s Algorithm to Drawing Straight Lines”.- “The Accuracy of the Digital Representation of a Straight Line”.- “Experience in Practical Implementation of Boundary-Defined Area Fill”.- “The Implementation of Fill Area for GKS”.- “A Simple Algorithm for Determining whether a Point Resides within an Arbitrarily Shaped Polygon”.- Section 2. Arcs, Circles and Conics.- Invited Papers.- “Algorithms for Circular Arc Generation”.- “Algorithms of Conic Generation”.- Submitted Papers.- “A High-Precision Digital Differential Analyzer for Circle Generation”.- “An Ellipse-Drawing Algorithm for Raster Displays”.- “An Algorithm for Determining the Draw Start Point of a Hyperbola given the System Direction of Draw and the Coordinates of the Video Window”.- Section 3. Curves and Curve Drawing.- Invited Papers.- “A Review of Curve Drawing Algorithms”.- “Methods for Drawing Curves”.- Submitted Paper.- “Generation of ?-Spline Curves using a Recurrence Relation”.- Section 4. Character Generation and Display.- Invited Papers.- “Character Generation and Display”.- “Font Information and Device-Independent Output”.- Section 5. Contouring and Surface Drawing.- Invited Papers.- “Contouring — the State of the Art”.- “A Review of Geostatistical Techniques for Contouring”.- “Algorithms for Three-Dimensional Interpolation between Planar Slices”.- Submitted Papers.- “GENSURF: A System for General Surface Definition and Manipulation”.- “An Interesting Modification to the Bresenham Algorithm for Hidden-Line Solution”.- “Efficient Hidden Line Removal for Surface Plots Utilising Raster Graphics”.- Section 6. Hardware Architectures and Algorithms.- Invited papers.- “Graphics Software Standards and their Evolution with Hardware Algorithms”.- “Hardware Enhancements for Raster Graphics”.- “Systolic Array Architectures for High Performance CAD/CAM Workstations”.- “Parallel Architectures for High Performance Graphics Systems”.- Section 7. Computational Geometry and CAD.- Invited Paper.- “Computational Geometry in Practice”.- Submitted Papers.- “An Algorithm for Direct Display of CSG Objects by Spatial Subdivision”.- “Computational Geometry and Prolog”.- “Subdivision Techniques for Processing Geometric Objects”.- Section 8. Theoretical Aspects and Models.- Invited Papers.- “Random Fractal Forgeries”.- “The Algebra of Algorithms”.- “Theoretical Considerations in Algorithm Design”.- “Technology for the Protection of Graphics Algorithms”.- “Spatial Concepts in 3D”.- Submitted Papers.- “Shortest Paths in 3-Space, Voronoi Diagrams with Barriers, and Related Complexity and Algebraic Issues”.- “Geometric Data Structures for Computer Graphics”.- “A Model for Raster Graphics Language Primitives”.- “Theoretical Framework for Shape Representation and Analysis”.- Section 9. Human-Computer Interface Issues.- Invited Papers.- “Aspects of Human Machine Interface”.- “Visual Perception and Computer Graphics”.- Section 10. Computer Animation.- Invited Paper.- “Object and Movement Description Techniques for Animation — An Informal Review”.- Scientific Organising Committee.- Lecturers.- Participants.
£42.74
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Algorithms and Data Structures: The Basic Toolbox
Book SynopsisAlgorithms are at the heart of every nontrivial computer application, and algorithmics is a modern and active area of computer science. Every computer scientist and every professional programmer should know about the basic algorithmic toolbox: structures that allow efficient organization and retrieval of data, frequently used algorithms, and basic techniques for modeling, understanding and solving algorithmic problems. This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, priority queues, sorted sequences, graph representation, graph traversal, shortest paths, minimum spanning trees, and optimization. The algorithms are presented in a modern way, with explicitly formulated invariants, and comment on recent trends such as algorithm engineering, memory hierarchies, algorithm libraries and certifying algorithms. The authors use pictures, words and high-level pseudocode to explain the algorithms, and then they present more detail on efficient implementations using real programming languages like C++ and Java. The authors have extensive experience teaching these subjects to undergraduates and graduates, and they offer a clear presentation, with examples, pictures, informal explanations, exercises, and some linkage to the real world. Most chapters have the same basic structure: a motivation for the problem, comments on the most important applications, and then simple solutions presented as informally as possible and as formally as necessary. For the more advanced issues, this approach leads to a more mathematical treatment, including some theorems and proofs. Finally, each chapter concludes with a section on further findings, providing views on the state of research, generalizations and advanced solutions.Trade Review"This is another mainstream textbook on algorithms and data structures, mainly intended for undergraduate students and professionals … . The two-layer index table is also detailed and helpful. I do enjoy reading the informative sections of historical notes and further findings at the end of each chapter. … This book is very well written, with the help of … clear figures and tables, as well as many interesting and inspiring examples." Zhizhang Shen, Zentralblatt MATH, Vol. 1146, 2008"... the book develops the basic fundamental principles underlying their design and analysis without sacrificing depth or rigor. The authors' insight, knowledge and active research on algorithms and data structures provide a very solid approach to the book. I particularly liked their "as informally as possible and as formally as necessary" writing style, and I enjoyed a lot their decision to not only discuss classical results, but to broaden the view to alternative implementations, memory hierarchies and libraries, which transmits novelty and increases interest...I think that this book will be a superb addition particularly useful for teachers of undergraduate courses, to graduate students in Computer Science, and to researchers that work, or intend to work, with algorithms." Jordi Petit, Computer Science Review 3, 2009 "Mehlhorn and Sanders write well, and the well-organized presentation reflects their experience and interest in the various topics... it is an excellent reference, and could possibly be used in a transition course, serving students coming to graduate CS courses from other technical fields. [...]This text is intended for undergraduate computer science (CS) majors, and focuses on algorithm analysis. … it is an excellent reference, and could possibly be used in a transition course, serving students coming to graduate CS courses from other technical fields. Finally, the book contains interesting tidbits that are not readily available elsewhere." M. G. Murphy, ACM Computing Reviews, October 2008"A 'Toolbox' should be portable, practical, and useful. This book is all these, covering a nice swath of the classic CS algorithms but addressing them in a way that is accessible to the student and practitioner. Furthermore, it manages to incorporate interesting examples as well as subtle examples of wit compressed into its 300 pages. Although it is not tied to any one language or library, it provides practical references to efficient open-source implementations of many of the algorithms and data structures; these should be the first refuge of the commercial developer. I can easily recommend this book as an intermediate undergraduate text, a refresher for those of us who only dimly remember our intermediate undergraduate courses, and as a reference for the professional development craftsman." Hal C. Elrod, SIGACT News Book Review Column 42(4) 2011Table of ContentsAppetizer: Integer Arithmetics.- Representing Sequences by Arrays and Linked Lists.- Hash Tables and Associative Arrays.- Sorting and Selection.- Priority Queues.- Sorted Sequences.- Graph Representation.- Graph Traversal.- Shortest Paths.- Minimum Spanning Trees.- Generic Approaches to Optimization.
£49.49
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Algorithmic Adventures: From Knowledge to Magic
Book SynopsisThe ?rst and foremost goal of this lecture series was to show the beauty, depth and usefulness of the key ideas in computer science. While working on the lecture notes, we came to understand that one can recognize the true spirit of a scienti?c discipline only by viewing its contributions in the framework of science as a whole. We present computer science here as a fundamental science that, interacting with other scienti?c disciplines, changed and changes our view on the world, that contributes to our understanding of the fundamental concepts of science and that sheds new light on and brings new meaning to several of these concepts. We show that computer science is a discipline that discovers spectacular, unexpected facts, that ?nds ways out in seemingly unsolvable s- uations, and that can do true wonders. The message of this book is that computer science is a fascinating research area with a big impact on the real world, full of spectacular ideas and great ch- lenges. It is an integral part of science and engineering with an above-average dynamic over the last 30 years and a high degree of interdisciplinarity. The goal of this book is not typical for popular science writing, whichoftenrestrictsitselftooutliningtheimportanceofaresearch area. Whenever possible we strive to bring full understanding of the concepts and results presented.Trade ReviewFrom the reviews: "A lucid exposition of fundamental ideas, concepts and methods of computer science, their essence and their limits, delightfully represented, and easily understandable for a broad readership. Scientific writing at its best." (Peter Widmayer, ETH Zürich)“This book originated from a series of lectures given by the author to describe what computer science is and what its principle Ideas are. Algorithms are the key concept of this book. … The inclusion of problems makes the book more than a personal reflection. The style is lively and avoids unnecessary jargon. With a good teacher, it could be suitable as a textbook on the foundations of computer science in an undergraduate classroom.” (Anthony J. Duben, ACM Computing Reviews, February, 2010)“This is a very readable book on theoretical computer science, written for nonspecialists. … Practical applications are illustrated by examples from DNA computing and quantum mechanics. … Summing Up: Recommended. Lower- and upper-division undergraduates and general readers.” (M. Bona, Choice, Vol. 47 (5), January, 2010)“The author is an acclaimed computer scientist and he proves why: apart from being an aggressive researcher, he is also an excellent teacher. Using his ability to teach complex computing topics in an interesting way, he introduces to the reader the ‘power and the magic’ of the underlying principles. … It will certainly draw interest from both undergraduate and post-graduate students of computing and allied fields. … I do recommend this beautiful book for a scientific library … .” (Soubhik Chakraborty, ACM Computing Reviews, August, 2010)Table of ContentsThe Development of Computer Science: Not Just a Driving Licence.- Algorithmics: What Programming and Baking Have in Common.- Infinity Is Not Infinity: Why Infinity Is Infinitely Important in Computer Science.- The Limits of Computability: Why There Exist Tasks That Cannot Be Automatically Solved Using Computers.- Complexity Theory: What to Do When the Energy of the Universe Isn't Enough to Perform a Computation.- Randomness in Nature: A Source of Efficiency in Algorithmics.- Cryptography: How to Transform Drawbacks into Advantages.- Computing Using DNA Molecules: A Biological Computer on the Horizon.- Quantum Computers: Computing in the Wonderland of Particles.- How to Make a Good Decision for an Unknown Future: How to Foil an Adversary
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