Mathematical theory of computation Books
Nova Science Publishers Inc Structured Matrices: Recent Developments in
Book SynopsisMatrices with structure are encountered in a wide variety of problems in pure and applied mathematics, and in engineering. Matrix patterns and structural properties provide a uniform means for describing apparently different features of the problems that they model. This book collects a set of contributions in structured matrix computations that covers different facets of the problems involved in this research area. The book may be naturally divided into four parts: the first part contains two contributions on asymptotical spectral properties of structured matrices. The second part contains seven contributions related to algorithm design and analysts. The third part, consisting of three contributions, concerns issues specifically related to structures, algebras and polynomials. The fourth part concerns applications to image processing and differential equations.
£85.59
Centre for the Study of Language & Information Advances in Modal Logic, Volume 2
Book SynopsisModal logic originated in philosophy as the logic of necessity and possibility. Now it has reached a high level of mathematical sophistication and has many applications in a variety of disciplines, ranging from artificial intelligence, computer science and mathematics via natural language syntax and semantics to philosophy. It is the main source of formal languages aimed at analyzing complex notions such as common knowlwdge and formal provability. This volume presents a broad, contemporary view of the field, with contributions covering the foundations of modal logic as well as its many application areas.
£32.67
AAAI Journal of Artificial Intelligence Research
Book Synopsis
£66.08
AAAI Proceedings of the Twenty-Seventh International
Book Synopsis
£94.02
AAAI Proceedings of the Thirtieth AAAI Conference on
Book Synopsis
£150.00
AAAI Proceedings of the Twenty-Fifth International
Book Synopsis
£150.00
AAAI Proceedings of the Thirty-First AAAI Conference
Book Synopsis
£150.00
Nova Science Publishers Inc Scientific Computing & Applications
Book SynopsisScientific Computing & Applications
£85.59
Society for Industrial & Applied Mathematics,U.S. First-Order Methods In Optimization
Book SynopsisThe primary goal of this book is to provide a self-contained, comprehensive study of the main ?rst-order methods that are frequently used in solving large-scale problems. First-order methods exploit information on values and gradients/subgradients (but not Hessians) of the functions composing the model under consideration. With the increase in the number of applications that can be modeled as large or even huge-scale optimization problems, there has been a revived interest in using simple methods that require low iteration cost as well as low memory storage.The author has gathered, reorganized, and synthesized (in a unified manner) many results that are currently scattered throughout the literature, many of which cannot be typically found in optimization books.First-Order Methods in Optimization offers comprehensive study of first-order methods with the theoretical foundations; provides plentiful examples and illustrations; emphasizes rates of convergence and complexity analysis of the main first-order methods used to solve large-scale problems; and covers both variables and functional decomposition methods.Table of Contents Preface; Chapter 1: Vector Spaces; Chapter 2: Extended Real-Value Functions; Chapter 3: Subgradients; Chapter 4: Conjugate Functions; Chapter 5: Smoothness and Strong Convexity; Chapter 6: The Proximal Operator; Chapter 7: Spectral Functions; Chapter 8: Primal and Dual Projected Subgradient Methods; Chapter 9: Mirror Descent; Chapter 10: The Proximal Gradient Method; Chapter 11: The Block Proximal Gradient Method; Chapter 12: Dual-Based Proximal Gradient Methods; Chapter 13: The Generalized Conditional Gradient Method; Chapter 14: Alternating Minimization; Chapter 15: ADMM; Appendix A: Strong Duality and Optimality Conditions; Appendix B: Tables; Appendix C: Symbols and Notation; Appendix D: Bibliographic Notes; Bibliography; Index.
£86.70
Society for Industrial & Applied Mathematics,U.S. Numerical Analysis of Partial Differential
Book SynopsisThis book provides an elementary yet comprehensive introduction to the numerical solution of partial differential equations (PDEs). Used to model important phenomena, such as the heating of apartments and the behavior of electromagnetic waves, these equations have applications in engineering and the life sciences, and most can only be solved approximately using computers.Numerical Analysis of Partial Differential Equations Using Maple and MATLAB provides detailed descriptions of the four major classes of discretization methods for PDEs (finite difference method, finite volume method, spectral method, and finite element method) and runnable MATLAB® code for each of the discretization methods and exercises. It also gives self-contained convergence proofs for each method using the tools and techniques required for the general convergence analysis but adapted to the simplest setting to keep the presentation clear and complete.This book is intended for advanced undergraduate and early graduate students in numerical analysis and scientific computing and researchers in related fields. It is appropriate for a course on numerical methods for partial differential equations.
£57.80
Society for Industrial & Applied Mathematics,U.S. Sparse Polynomial Approximation of
Book SynopsisOver seventy years ago, Richard Bellman coined the term "the curse of dimensionality" to describe phenomena and computational challenges that arise in high dimensions. These challenges, in tandem with the ubiquity of high-dimensional functions in real-world applications, have led to a lengthy, focused research effort on high-dimensional approximation—that is, the development of methods for approximating functions of many variables accurately and efficiently from data. This book provides an in-depth treatment of one of the latest installments in this long and ongoing story: sparse polynomial approximation methods. These methods have emerged as useful tools for various high-dimensional approximation tasks arising in a range of applications in computational science and engineering. It begins with a comprehensive overview of best s-term polynomial approximation theory for holomorphic, high-dimensional functions, as well as a detailed survey of applications to parametric differential equations. It then describes methods for computing sparse polynomial approximations, focusing on least squares and compressed sensing techniques.Sparse Polynomial Approximation of High-Dimensional Functions presents the first comprehensive and unified treatment of polynomial approximation techniques that can mitigate the curse of dimensionality in high-dimensional approximation, including least squares and compressed sensing. It develops main concepts in a mathematically rigorous manner, with full proofs given wherever possible, and it contains many numerical examples, each accompanied by downloadable code. The authors provide an extensive bibliography of over 350 relevant references, with an additional annotated bibliography available on the book's companion website (www.sparse-hd-book.com).This text is aimed at graduate students, postdoctoral fellows, and researchers in mathematics, computer science, and engineering who are interested in high-dimensional polynomial approximation techniques.
£71.40
Nova Science Publishers Inc Statistical & Soft Computing Approaches in
Book SynopsisThis book reviews the application of different statistical and Soft-Computing (SC) techniques in insurance-related problems. The book has been divided into 5 chapters, with the following structure: Chapter 1 provides a comprehensive review of SC techniques in insurance problems. A review of the application of these methods in insurance problems and a case study in a real problem completes this first chapter. Chapters 2 and 3 describe two different real applications of SC techniques in insurance. In this chapter, the authors describe the main concepts related to the algorithm and discuss different application of the algorithm in the insurance sector. Chapter 3 is devoted to a state-of-the-art technique in neural computation (Support Vector Machines, SVM). Chapter 4 presents a new mathematical tool based on modal intervals that allow us to process interval data (reflecting the fact that the data we are working with is not exact) and to interpret semantically the results obtained. Chapter 5 concentrates on two well-known risk measures: the Value at Risk and the Tail Value at Risk. The authors present a new analytical expression of the Tail Value at Risk using the Normal-Power approximation and they analyse its precision.
£63.74
now publishers Inc User-friendly Introduction to PAC-Bayes Bounds
Book SynopsisProbably almost correct (PAC) bounds have been an intensive field of research over the last two decades. Hundreds of papers have been published and much progress has been made resulting in PAC-Bayes bounds becoming an important technique in machine learning.The proliferation of research has made the field for a newcomer somewhat daunting. In this tutorial, the author guides the reader through the topic’s complexity and large body of publications. Covering both empirical and oracle PAC-bounds, this book serves as a primer for students and researchers who want to get to grips quickly with the subject. It provides a friendly introduction that illuminates the basic theory and points to the most important publications to gain deeper understanding of any particular aspect.Table of Contents 1. Introduction 2. First Step in the PAC-Bayes World 3. Tight and Non-vacuous PAC-Bayes Bounds 4. PAC-Bayes Oracle Inequalities and Fast Rates 5. Beyond “Bounded Loss” and “i.i.d. Observations” 6. Related Approaches in Statistics and Machine Learning Theory 7. Conclusion Acknowledgements References
£76.95
Willford Press Fundamentals of Machine Learning
Book Synopsis
£103.95
now publishers Inc Graph Kernels: State-of-the-Art and Future
Book SynopsisAmong the data structures commonly used in machine learning, graphs are arguably one of the most general. Graphs allow the modelling of complex objects, each of which can be annotated by metadata. Nonetheless, seemingly simple questions, such as determining whether two graphs are identical or whether one graph is contained in another graph, are remarkably hard to solve in practice. Machine learning methods operating on graphs must therefore grapple with the need to balance computational tractability with the ability to leverage as much of the information conveyed by each graph as possible. In the last 15 years, numerous graph kernels have been proposed to solve this problem, thereby making it possible to perform predictions in both classification and regression settings.This monograph provides a review of existing graph kernels, their applications, software plus data resources, and an empirical comparison of state-of-the-art graph kernels. It is divided into two parts: the first part focuses on the theoretical description of common graph kernels; the second part focuses on a large-scale empirical evaluation of graph kernels, as well as a description of desirable properties and requirements for benchmark data sets. Finally, the authors outline the future trends and open challenges for graph kernels. Written for every researcher, practitioner and student of machine learning, Graph Kernels provides a comprehensive and insightful survey of the various graph kernals available today. It gives the reader a detailed typology, and analysis of relevant graph kernels while exposing the relations between them and commenting on their applicability for specific data types. There is also a large-scale empirical evaluation of graph kernels.Table of Contents 1. Introduction 2. Background on graph comparison and kernel methods 3. Kernels for graph-structured data 4. Experimental evaluation of graph kernels 5. Discussion & future directions 6. Accompanying website Glossary References
£63.75
Rowman & Littlefield International Desire After Affect
Book SynopsisDesire is a term often used in conjunction with the subject. This desire is directed towards the real, which is defined as the generic core of the linguistic order. As a result of the focus on affect, the three terms—desire, the subject, the real—have been fundamentally shaken up and called into question. Affect, in various forms, is now a matter of concern across a wide range of disciplines including neuroscience, psychology, the humanities, and social sciences. All of these fields have a declared interest in affect, in emotions and sensations, in pathos, passions, and the senses. Desire After Affect argues that this affective euphoria cannot be explained solely in terms of a repression of language, logos, and reason. It argues that the affective turn is symptomatic of a fundamental shift in modes of thinking about the human condition. It explores what this means for the human and the posthuman, animal and machine, and calls for a new theory of subjectivation, a philosophy of media affect. Trade ReviewDesire After Affect offers a strong analysis how affect has been placed at the centre of posthuman theory. Angerer’s take is reflective, clear and inspiring in how it shows the nuances of the concept that marks a historical shift from psychoanalysis to neurosciences. The book is of high relevance to scholars in media, contemporary arts and cultural theory. -- Jussi Parikka, Professor in Technological Culture and Aesthetics, University of SouthamptonForget the cognitive revolution, think affect. Marie-Luise Angerer is very convincing in her study of affect and desire, describing what most of us are aware of without being able to explain it (which is a perfect illustration of the book): subjectivity and eroticism are changing, art and media are showing the way. Based on a very thorough study, drawing on authors ranging from Helmholtz to Malabou, with Freud, Lacan, Deleuze and Braidotti in between, this book presents the reader with an uncanny mirror image. ‘I am what the cyborg feels’ might become the new cogito. -- Paul Verhaeghe, Head of the Department of Psychoanalysis and Clinical Consulting at Ghent University and author of What About Me?Desire After Affect represents a major intervention into one of the leading debates in the Humanities today. Translating and extending the original German version published in 2007, this English edition arrives at a timely moment of critical reflection on the so-called ‘affective turn’, which looks increasingly like an epistemological break. If sexuality was diagnosed by Foucault as the organising discourse of human subjectivity in the nineteenth and twentieth centuries, Marie-Luise Angerer examines how and why ‘affect’ has become its replacement in the twenty-first. Rather than running towards the bright lights of the promise of affect, as so many other have done, Angerer situates its discursive legacies within an unlikely convergence of very different theoretical frameworks, cautioning us to consider some of its more troubling implications. Displaying a breath-taking range of knowledge of critical theory, philosophy and psychoanalysis, this book speaks to a significant challenge to the terms of knowledge production across the arts and the sciences. Delivered with clarity and precision, yet always expansive in its terms of reference, Angerer’s book is a welcome intervention into this contested field of enquiry. -- Jackie Stacey, Professor of Media and Cultural Studies and Director of the Centre for Interdisciplinary Research in the Arts and Languages (CIDRAL) at the University of ManchesterEach chapter of Desire After Affect analyses the dispositif of affect from a different angle. The somatic turn, the human/posthuman/transhuman debate, neurobiology, sex, the digital and the unconscious are woven together in the attempt to argue for the replacing of the sexual subject altogether in favour of affect, and the uncovering of desire ‘after’ affect as momentary time lag or temporal gap […]The temporal gap of reaction – the ‘moment of a half-second’ – is Angerer’s locus of desire ‘after’ affect, and the conceptual work done to reach this climactic point is impressive indeed. * Radical Philosophy *Table of ContentsAcknowledgments/ Foreword by Patricia T. Clough/ Introduction/ 1 Affective Troubles in Media and Art/ 2 Human / Posthuman/Transhuman/ 3 Affect versus Drive, or the Battle over Representation/ 4 Virtual Sex and Other Metamorphoses/5 Sexualizing Affect/ Postscript: A New Affective Organization/ Bibliography/ Index
£100.80
Rowman & Littlefield International Desire After Affect
Book SynopsisDesire is a term often used in conjunction with the subject. This desire is directed towards the real, which is defined as the generic core of the linguistic order. As a result of the focus on affect, the three terms—desire, the subject, the real—have been fundamentally shaken up and called into question. Affect, in various forms, is now a matter of concern across a wide range of disciplines including neuroscience, psychology, the humanities, and social sciences. All of these fields have a declared interest in affect, in emotions and sensations, in pathos, passions, and the senses. Desire After Affect argues that this affective euphoria cannot be explained solely in terms of a repression of language, logos, and reason. It argues that the affective turn is symptomatic of a fundamental shift in modes of thinking about the human condition. It explores what this means for the human and the posthuman, animal and machine, and calls for a new theory of subjectivation, a philosophy of media affect. Trade ReviewDesire After Affect offers a strong analysis how affect has been placed at the centre of posthuman theory. Angerer’s take is reflective, clear and inspiring in how it shows the nuances of the concept that marks a historical shift from psychoanalysis to neurosciences. The book is of high relevance to scholars in media, contemporary arts and cultural theory. -- Jussi Parikka, Professor in Technological Culture and Aesthetics, University of SouthamptonForget the cognitive revolution, think affect. Marie-Luise Angerer is very convincing in her study of affect and desire, describing what most of us are aware of without being able to explain it (which is a perfect illustration of the book): subjectivity and eroticism are changing, art and media are showing the way. Based on a very thorough study, drawing on authors ranging from Helmholtz to Malabou, with Freud, Lacan, Deleuze and Braidotti in between, this book presents the reader with an uncanny mirror image. ‘I am what the cyborg feels’ might become the new cogito. -- Paul Verhaeghe, Head of the Department of Psychoanalysis and Clinical Consulting at Ghent University and author of What About Me?Desire After Affect represents a major intervention into one of the leading debates in the Humanities today. Translating and extending the original German version published in 2007, this English edition arrives at a timely moment of critical reflection on the so-called ‘affective turn’, which looks increasingly like an epistemological break. If sexuality was diagnosed by Foucault as the organising discourse of human subjectivity in the nineteenth and twentieth centuries, Marie-Luise Angerer examines how and why ‘affect’ has become its replacement in the twenty-first. Rather than running towards the bright lights of the promise of affect, as so many other have done, Angerer situates its discursive legacies within an unlikely convergence of very different theoretical frameworks, cautioning us to consider some of its more troubling implications. Displaying a breath-taking range of knowledge of critical theory, philosophy and psychoanalysis, this book speaks to a significant challenge to the terms of knowledge production across the arts and the sciences. Delivered with clarity and precision, yet always expansive in its terms of reference, Angerer’s book is a welcome intervention into this contested field of enquiry. -- Jackie Stacey, Professor of Media and Cultural Studies and Director of the Centre for Interdisciplinary Research in the Arts and Languages (CIDRAL) at the University of ManchesterEach chapter of Desire After Affect analyses the dispositif of affect from a different angle. The somatic turn, the human/posthuman/transhuman debate, neurobiology, sex, the digital and the unconscious are woven together in the attempt to argue for the replacing of the sexual subject altogether in favour of affect, and the uncovering of desire ‘after’ affect as momentary time lag or temporal gap […]The temporal gap of reaction – the ‘moment of a half-second’ – is Angerer’s locus of desire ‘after’ affect, and the conceptual work done to reach this climactic point is impressive indeed. * Radical Philosophy *Table of ContentsAcknowledgments/ Foreword by Patricia T. Clough/ Introduction/ 1 Affective Troubles in Media and Art/ 2 Human / Posthuman/Transhuman/ 3 Affect versus Drive, or the Battle over Representation/ 4 Virtual Sex and Other Metamorphoses/5 Sexualizing Affect/ Postscript: A New Affective Organization/ Bibliography/ Index
£36.10
ISTE Ltd and John Wiley & Sons Inc The Uncertain Digital Revolution
Book SynopsisDigital information and communication technologies can be seen as a threat to privacy, a step forward for freedom of expression and communication, a tool in the fight against terrorism or the source of a new economic wealth. Computerization has unexpectedly progressed beyond our imagination, from a tool of management and control into one of widespread communication and expression. This book revisits the major questions that have emerged with the progress of computerization over nearly half a century, by describing the context in which these issues were formulated. By taking a social and digital approach, the author explores controversial issues surrounding the development of this "digital revolution", including freedom and privacy of the individual, social control, surveillance, public security and the economic exploitation of personal data. From students, teachers and researchers engaged in data analysis, to institutional decision-makers and actors in policy or business, all members of today's digital society will take from this book a better understanding of the essential issues of the current "digital revolution".Table of ContentsIntroduction ix Chapter 1. Technological Surveillance Subjected to Restrictions 1 Chapter 2. Security Over Liberty 21 Chapter 3. A Network Promoting Participation and Exchange 41 Chapter 4. Privitization and Economic Exploitation of Personal Data 65 Chapter 5. Digitalization and Revolution 87 Bibliography 107 Index 117
£125.06
Springer London Ltd Semantics with Applications: An Appetizer
Book SynopsisSemantics will play an important role in the future development of software systems and domain-specific languages. This book provides a needed introductory presentation of the fundamental ideas behind these approaches, stresses their relationship by formulating and proving the relevant theorems, and illustrates the applications of semantics in computer science. Historically important application areas are presented together with some exciting potential applications. The text investigates the relationship between various methods and describes some of the main ideas used, illustrating these by means of interesting applications. The book provides a rigorous introduction to the main approaches to formal semantics of programming languages.Trade ReviewFrom the reviews: "This book title, with its explicit reference to applications, quickly grabbed my attention due to the theoretical nature of formal semantics. … In any case, this book certainly fits the bill for an undergraduate course on the topic. … It also includes plenty of solved examples and exercises for students to help them grasp the key ideas and techniques behind the different mathematical models that can be used to describe the computations performed by a computer program." (Fernando Berzal, Computing Reviews, January, 2008) "This book presents a rigorous introduction to the main three approaches: operational semantics, denotational semantics, and axiomatic semantics. This book investigates the relationship between the various methods, and describes some of the main ideas by using applications. … Several exercises are provided. … help the student to understand definitions, results, and techniques … ." (G. Ciobanu, ACM Computing Reviews, May, 2009)Table of ContentsOperational Semantics.- More on Operational Semantics.- Provably Correct Implementation.- Denotational Semantics.- More on Denotational Semantics.- Program Analysis.- More on Program Analysis.- Axiomatic Program Verification.- More on Axiomatic Program Verification.- Further Reading.
£26.99
Imperial College Press Computability In Context: Computation And Logic
Book SynopsisComputability has played a crucial role in mathematics and computer science, leading to the discovery, understanding and classification of decidable/undecidable problems, paving the way for the modern computer era, and affecting deeply our view of the world. Recent new paradigms of computation, based on biological and physical models, address in a radically new way questions of efficiency and challenge assumptions about the so-called Turing barrier.This volume addresses various aspects of the ways computability and theoretical computer science enable scientists and philosophers to deal with mathematical and real-world issues, covering problems related to logic, mathematics, physical processes, real computation and learning theory. At the same time it will focus on different ways in which computability emerges from the real world, and how this affects our way of thinking about everyday computational issues.
£121.50
ISTE Ltd and John Wiley & Sons Inc Formal Languages, Automata and Numeration Systems
Book SynopsisFormal Languages, Automaton and Numeration Systems presents readers with a review of research related to formal language theory, combinatorics on words or numeration systems, such as Words, DLT (Developments in Language Theory), ICALP, MFCS (Mathematical Foundation of Computer Science), Mons Theoretical Computer Science Days, Numeration, CANT (Combinatorics, Automata and Number Theory). Combinatorics on words deals with problems that can be stated in a non-commutative monoid, such as subword complexity of finite or infinite words, construction and properties of infinite words, unavoidable regularities or patterns. When considering some numeration systems, any integer can be represented as a finite word over an alphabet of digits. This simple observation leads to the study of the relationship between the arithmetical properties of the integers and the syntactical properties of the corresponding representations. One of the most profound results in this direction is given by the celebrated theorem by Cobham. Surprisingly, a recent extension of this result to complex numbers led to the famous Four Exponentials Conjecture. This is just one example of the fruitful relationship between formal language theory (including the theory of automata) and number theory.Trade Review"This nice book is devoted to a quickly growing field, at the frontier between theoretical computer science, combinatorics, and number theory." (Zentralblatt MATH, 2016)Table of ContentsFOREWORD ix INTRODUCTION xiii CHAPTER 1. WORDS AND SEQUENCES FROM SCRATCH 1 1.1. Mathematical background and notation 2 1.1.1. About asymptotics 4 1.1.2. Algebraic number theory 5 1.2. Structures, words and languages 11 1.2.1. Distance and topology 16 1.2.2. Formal series 24 1.2.3. Language, factor and frequency 28 1.2.4. Period and factor complexity 33 1.3. Examples of infinite words 36 1.3.1. About cellular automata 43 1.3.2. Links with symbolic dynamical systems 46 1.3.3. Shift and orbit closure 59 1.3.4. First encounter with β-expansions 62 1.3.5. Continued fractions 69 1.3.6. Direct product, block coding and exercises 70 1.4. Bibliographic notes and comments 77 CHAPTER 2. MORPHIC WORDS 85 2.1. Formal definitions 89 2.2. Parikh vectors and matrices associated with a morphism 96 2.2.1. The matrix associated with a morphism 98 2.2.2. The tribonacci word 99 2.3. Constant-length morphisms 107 2.3.1. Closure properties 117 2.3.2. Kernel of a sequence 119 2.3.3. Connections with cellular automata 120 2.4. Primitive morphisms 122 2.4.1. Asymptotic behavior 127 2.4.2. Frequencies and occurrences of factors 127 2.5. Arbitrary morphisms 133 2.5.1. Irreducible matrices 134 2.5.2. Cyclic structure of irreducible matrices 144 2.5.3. Proof of theorem 2.35 150 2.6. Factor complexity and Sturmian words 153 2.7. Exercises 159 2.8. Bibliographic notes and comments 163 CHAPTER 3. MORE MATERIAL ON INFINITE WORDS 173 3.1. Getting rid of erasing morphisms 174 3.2. Recurrence 185 3.3. More examples of infinite words 191 3.4. Factor Graphs and special factors 202 3.4.1. de Bruijn graphs 202 3.4.2. Rauzy graphs 206 3.5. From the Thue–Morse word to pattern avoidance 219 3.6. Other combinatorial complexity measures 228 3.6.1. Abelian complexity 228 3.6.2. k-Abelian complexity 237 3.6.3. k-Binomial complexity 245 3.6.4. Arithmetical complexity 249 3.6.5. Pattern complexity 251 3.7. Bibliographic notes and comments 252 BIBLIOGRAPHY 257 INDEX 295 SUMMARY OF VOLUME 2 303
£125.06
Springer London Ltd Understanding Concurrent Systems
Book SynopsisCSP notation has been used extensively for teaching and applying concurrency theory, ever since the publication of the text Communicating Sequential Processes by C.A.R. Hoare in 1985. Both a programming language and a specification language, the theory of CSP helps users to understand concurrent systems, and to decide whether a program meets its specification. As a member of the family of process algebras, the concepts of communication and interaction are presented in an algebraic style. An invaluable reference on the state of the art in CSP, Understanding Concurrent Systems also serves as a comprehensive introduction to the field, in addition to providing material for a number of more advanced courses. A first point of reference for anyone wanting to use CSP or learn about its theory, the book also introduces other views of concurrency, using CSP to model and explain these. The text is fully integrated with CSP-based tools such as FDR, and describes how to create new tools based on FDR. Most of the book relies on no theoretical background other than a basic knowledge of sets and sequences. Sophisticated mathematical arguments are avoided whenever possible. Topics and features: presents a comprehensive introduction to CSP; discusses the latest advances in CSP, covering topics of operational semantics, denotational models, finite observation models and infinite-behaviour models, and algebraic semantics; explores the practical application of CSP, including timed modelling, discrete modelling, parameterised verifications and the state explosion problem, and advanced topics in the use of FDR; examines the ability of CSP to describe and enable reasoning about parallel systems modelled in other paradigms; covers a broad variety of concurrent systems, including combinatorial, timed, priority-based, mobile, shared variable, statecharts, buffered and asynchronous systems; contains exercises and case studies to support the text; supplies further tools and information at the associated website: http://www.comlab.ox.ac.uk/ucs/. From undergraduate students of computer science in need of an introduction to the area, to researchers and practitioners desiring a more in-depth understanding of theory and practice of concurrent systems, this broad-ranging text/reference is essential reading for anyone interested in Hoare’s CSP.Trade ReviewFrom the reviews:“This book is divided into four parts … . Part I is designed for an audience of both undergraduate and graduate computer science students. … Part II is designed for people who are familiar with Part I and have fairly theoretical interests. … Part III is intended for people who … want to be able to use them in a better way, or who are specifically interested in timed systems. Part IV is designed for people who already understand CSP.” (Günther Bauer, Zentralblatt MATH, Vol. 1211, 2011)Table of ContentsPart I: A Foundation Course in CSP Building a Simple Sequential Process Understanding CSP Parallel Operators CSP Case Studies Hiding and Renaming Beyond Traces Further Operators Using FDR Part II: Theory Operational Semantics Denotational Semantics and Behavioural Models Finite Observation Models Infinite-behaviour Models The Algebra of CSP Part III: Using CSP Timed Systems 1: tock-CSP Timed Systems 2: Discrete Timed CSP More About FDR State Explosion and Parameterised Verification Part IV: Exploring Concurrency Shared-variable Programs Understanding Shared-variable Concurrency Priority and Mobility
£40.49
Springer London Ltd Computational Methods in Biometric Authentication: Statistical Methods for Performance Evaluation
Book SynopsisBiometrics, the science of using physical traits to identify individuals, is playing an increasing role in our security-conscious society and across the globe. Biometric authentication, or bioauthentication, systems are being used to secure everything from amusement parks to bank accounts to military installations. Yet developments in this field have not been matched by an equivalent improvement in the statistical methods for evaluating these systems. Compensating for this need, this unique text/reference provides a basic statistical methodology for practitioners and testers of bioauthentication devices, supplying a set of rigorous statistical methods for evaluating biometric authentication systems. This framework of methods can be extended and generalized for a wide range of applications and tests. This is the first single resource on statistical methods for estimation and comparison of the performance of biometric authentication systems. The book focuses on six common performance metrics: for each metric, statistical methods are derived for a single system that incorporates confidence intervals, hypothesis tests, sample size calculations, power calculations and prediction intervals. These methods are also extended to allow for the statistical comparison and evaluation of multiple systems for both independent and paired data. Topics and features: * Provides a statistical methodology for the most common biometric performance metrics: failure to enroll (FTE), failure to acquire (FTA), false non-match rate (FNMR), false match rate (FMR), and receiver operating characteristic (ROC) curves * Presents methods for the comparison of two or more biometric performance metrics * Introduces a new bootstrap methodology for FMR and ROC curve estimation * Supplies more than 120 examples, using publicly available biometric data where possible * Discusses the addition of prediction intervals to the bioauthentication statistical toolset * Describes sample-size and power calculations for FTE, FTA, FNMR and FMR Researchers, managers and decisions makers needing to compare biometric systems across a variety of metrics will find within this reference an invaluable set of statistical tools. Written for an upper-level undergraduate or master’s level audience with a quantitative background, readers are also expected to have an understanding of the topics in a typical undergraduate statistics course. Dr. Michael E. Schuckers is Associate Professor of Statistics at St. Lawrence University, Canton, NY, and a member of the Center for Identification Technology Research.Table of ContentsPart I: Introduction Introduction Statistical Background Part II: Primary Matching and Classification Measures False Non-Match Rate False Match Rate Receiver Operating Characteristic Curve and Equal Error Rate Part III: Biometric Specific Measures Failure to Enrol Failure to Acquire Part IV: Additional Topics and Appendices Additional Topics and Discussion Tables
£123.49
Springer London Ltd Geometric Algebra for Computer Graphics
Book SynopsisGeometric algebra (a Clifford Algebra) has been applied to different branches of physics for a long time but is now being adopted by the computer graphics community and is providing exciting new ways of solving 3D geometric problems. The author tackles this complex subject with inimitable style, and provides an accessible and very readable introduction. The book is filled with lots of clear examples and is very well illustrated. Introductory chapters look at algebraic axioms, vector algebra and geometric conventions and the book closes with a chapter on how the algebra is applied to computer graphics.Table of ContentsElementary Algebra.- Complex Algebra.- Vector Algebra.- Quaternion Algebra.- Geometric Conventions.- Geometric Algebra.- The Geometric Product.- Reflections and Rotations.- Geometric Algebra and Geometry.- Conformal Geometry.- Applications of Geometric Algebra.- Programming Tools for Geometric Algebra.- Conclusion.
£42.75
Springer London Ltd Applied Interval Analysis: With Examples in Parameter and State Estimation, Robust Control and Robotics
Book SynopsisAt the core of many engineering problems is the solution of sets of equa tions and inequalities, and the optimization of cost functions. Unfortunately, except in special cases, such as when a set of equations is linear in its un knowns or when a convex cost function has to be minimized under convex constraints, the results obtained by conventional numerical methods are only local and cannot be guaranteed. This means, for example, that the actual global minimum of a cost function may not be reached, or that some global minimizers of this cost function may escape detection. By contrast, interval analysis makes it possible to obtain guaranteed approximations of the set of all the actual solutions of the problem being considered. This, together with the lack of books presenting interval techniques in such a way that they could become part of any engineering numerical tool kit, motivated the writing of this book. The adventure started in 1991 with the preparation by Luc Jaulin of his PhD thesis, under Eric Walter's supervision. It continued with their joint supervision of Olivier Didrit's and Michel Kieffer's PhD theses. More than two years ago, when we presented our book project to Springer, we naively thought that redaction would be a simple matter, given what had already been achieved . . .Trade ReviewFrom the reviews:"Applied Interval Analysis is the right book at the right time to move computing with intervals into the mainstream of engineering, financial, and scientific computing."G. William Walster, Interval Technology Engineering Manager, Sun Microsystems and Member of the Editorial Board of Reliable ComputingTable of ContentsI. Introduction.- 1. Introduction.- 1.1 What Are the Key Concepts?.- 1.2 How Did the Story Start?.- 1.3 What About Complexity?.- 1.4 How is the Book Organized?.- II. Tools.- 2. Interval Analysis.- 2.1 Introduction.- 2.2 Operations on Sets.- 2.2.1 Purely set-theoretic operations.- 2.2.2 Extended operations.- 2.2.3 Properties of set operators.- 2.2.4 Wrappers.- 2.3 Interval Analysis.- 2.3.1 Intervals.- 2.3.2 Interval computation.- 2.3.3 Closed intervals.- 2.3.4 Interval vectors.- 2.3.5 Interval matrices.- 2.4 Inclusion Functions.- 2.4.1 Definitions.- 2.4.2 Natural inclusion functions.- 2.4.3 Centred inclusion functions.- 2.4.4 Mixed centred inclusion functions.- 2.4.5 Taylor inclusion functions.- 2.4.6 Comparison.- 2.5 Inclusion Tests.- 2.5.1 Interval Booleans.- 2.5.2 Tests.- 2.5.3 Inclusion tests for sets.- 2.6 Conclusions.- 3. Subpavings.- 3.1 Introduction.- 3.2 Set Topology.- 3.2.1 Distances between compact sets.- 3.2.2 Enclosure of compact sets between subpavings.- 3.3 Regular Subpavings.- 3.3.1 Pavings and subpavings.- 3.3.2 Representing a regular subpaving as a binary tree.- 3.3.3 Basic operations on regular subpavings.- 3.4 Implementation of Set Computation.- 3.4.1 Set inversion.- 3.4.2 Image evaluation.- 3.5 Conclusions.- 4. Contractors.- 4.1 Introduction.- 4.2 Basic Contractors.- 4.2.1 Finite subsolvers.- 4.2.2 Intervalization of finite subsolvers.- 4.2.3 Fixed-point methods.- 4.2.4 Forward—backward propagation.- 4.2.5 Linear programming approach.- 4.3 External Approximation.- 4.3.1 Principle.- 4.3.2 Preconditioning.- 4.3.3 Newton contractor.- 4.3.4 Parallel linearization.- 4.3.5 Using formal transformations.- 4.4 Collaboration Between Contractors.- 4.4.1 Principle.- 4.4.2 Contractors and inclusion functions.- 4.5 Contractors for Sets.- 4.5.1 Definitions.- 4.5.2 Sets defined by equality and inequality constraints.- 4.5.3 Improving contractors using local search.- 4.6 Conclusions.- 5. Solvers.- 5.1 Introduction.- 5.2 Solving Square Systems of Non-linear Equations.- 5.3 Characterizing Sets Defined by Inequalities.- 5.4 Interval Hull of a Set Defined by Inequalities.- 5.4.1 First approach.- 5.4.2 Second approach.- 5.5 Global Optimization.- 5.5.1 The Moore—Skelboe algorithm.- 5.5.2 Hansen’s algorithm.- 5.5.3 Using interval constraint propagation.- 5.6 Minimax Optimization.- 5.6.1 Unconstrained case.- 5.6.2 Constrained case.- 5.6.3 Dealing with quantifiers.- 5.7 Cost Contours.- 5.8 Conclusions.- III. Applications.- 6. Estimation.- 6.1 Introduction.- 6.2 Parameter Estimation Via Optimization.- 6.2.1 Least-square parameter estimation in compartmental modelling.- 6.2.2 Minimax parameter estimation.- 6.3 Parameter Bounding.- 6.3.1 Introduction.- 6.3.2 The values of the independent variables are known.- 6.3.3 Robustification against outliers.- 6.3.4 The values of the independent variables are uncertain.- 6.3.5 Computation of the interval hull of the posterior feasible set.- 6.4 State Bounding.- 6.4.1 Introduction.- 6.4.2 Bounding the initial state.- 6.4.3 Bounding all variables.- 6.4.4 Bounding by constraint propagation.- 6.5 Conclusions.- 7. Robust Control.- 7.1 Introduction.- 7.2 Stability of Deterministic Linear Systems.- 7.2.1 Characteristic polynomial.- 7.2.2 Routh criterion.- 7.2.3 Stability degree.- 7.3 Basic Tests for Robust Stability.- 7.3.1 Interval polynomials.- 7.3.2 Polytope polynomials.- 7.3.3 Image-set polynomials.- 7.3.4 Conclusion.- 7.4 Robust Stability Analysis.- 7.4.1 Stability domains.- 7.4.2 Stability degree.- 7.4.3 Value-set approach.- 7.4.4 Robust stability margins.- 7.4.5 Stability radius.- 7.5 Controller Design.- 7.6 Conclusions.- 8. Robotics.- 8.1 Introduction.- 8.2 Forward Kinematics Problem for Stewart—Gough Platforms.- 8.2.1 Stewart—Gough platforms.- 8.2.2 From the frame of the mobile plate to that of the base.- 8.2.3 Equations to be solved.- 8.2.4 Solution.- 8.3 Path Planning.- 8.3.1 Graph discretization of configuration space.- 8.3.2 Algorithms for finding a feasible path.- 8.3.3 Test case.- 8.4 Localization and Tracking of a Mobile Robot.- 8.4.1 Formulation of the static localization problem.- 8.4.2 Model of the measurement process.- 8.4.3 Set inversion.- 8.4.4 Dealing with outliers.- 8.4.5 Static localization example.- 8.4.6 Tracking.- 8.4.7 Example.- 8.5 Conclusions.- IV. Implementation.- 9. Automatic Differentiation.- 9.1 Introduction.- 9.2 Forward and Backward Differentiations.- 9.2.1 Forward differentiation.- 9.2.2 Backward differentiation.- 9.3 Differentiation of Algorithms.- 9.3.1 First assumption.- 9.3.2 Second assumption.- 9.3.3 Third assumption.- 9.4 Examples.- 9.4.1 Example 1.- 9.4.2 Example 2.- 9.5 Conclusions.- 10. Guaranteed Computation with Floating-point Numbers.- 10.1 Introduction.- 10.2 Floating-point Numbers and IEEE 754.- 10.2.1 Representation.- 10.2.2 Rounding.- 10.2.3 Special quantities.- 10.3 Intervals and IEEE 754.- 10.3.1 Machine intervals.- 10.3.2 Closed interval arithmetic.- 10.3.3 Handling elementary functions.- 10.3.4 Improvements.- 10.4 Interval Resources.- 10.5 Conclusions.- 11. Do It Yourself.- 11.1 Introduction.- 11.2 Notions of C++.- 11.2.1 Program structure.- 11.2.2 Standard types.- 11.2.3 Pointers.- 11.2.4 Passing parameters to a function.- 11.3 INTERVAL Class.- 11.3.1 Constructors and destructor.- 11.3.2 Other member functions.- 11.3.3 Mathematical functions.- 11.4 Intervals with PROFIL/BIAS.- 11.4.1 BIAS.- 11.4.2 PROFIL.- 11.4.3 Getting started.- 11.5 Exercises on Intervals.- 11.6 Interval Vectors.- 11.6.1 INTERVAL_VECTOR class.- 11.6.2 Constructors, assignment and function call operators.- 11.6.3 Friend functions.- 11.6.4 Utilities.- 11.7 Vectors with PROFIL/BIAS.- 11.8 Exercises on Interval Vectors.- 11.9 Interval Matrices.- 11.10 Matrices with PROFIL/BIAS.- 11.11 Exercises on Interval Matrices.- 11.12 Regular Subpavings with PROFIL/BIAS.- 11.12.1 NODE class.- 11.12.2 Set inversion with subpavings.- 11.12.3 Image evaluation with subpavings.- 11.12.4 System simulation and state estimation with subpavings.- 11.13 Error Handling.- 11.13.1 Using exit.- 11.13.2 Exception handling.- 11.13.3 Mathematical errors.- References.
£85.49
AU Press Mind, Body, World: Foundations of Cognitive
Book SynopsisCognitive science arose in the 1950s when it became apparent that anumber of disciplines, including psychology, computer science,linguistics, and philosophy, were fragmenting. Perhaps owing to thefield’s immediate origins in cybernetics, as well as to thefoundational assumption that cognition is information processing,cognitive science initially seemed more unified than psychology.However, as a result of differing interpretations of the foundationalassumption and dramatically divergent views of the meaning of the terminformation processing, three separate schools emerged:classical cognitive science, connectionist cognitive science, andembodied cognitive science. Examples, cases, and research findings taken from the wide range ofphenomena studied by cognitive scientists effectively explain andexplore the relationship among the three perspectives. Intended tointroduce both graduate and senior undergraduate students to thefoundations of cognitive science, Mind, Body, World addressesa number of questions currently being asked by those practicing in thefield: What are the core assumptions of the three different schools?What are the relationships between these different sets of coreassumptions? Is there only one cognitive science, or are there manydifferent cognitive sciences? Giving the schools equal treatment anddisplaying a broad and deep understanding of the field, Dawsonhighlights the fundamental tensions and lines of fragmentation thatexist among the schools and provides a refreshing and unifyingframework for students of cognitive science.Table of ContentsList of Figures and Tables | ix Preface | xiii Who Is This Book Written For? | xiv Acknowledgements | xv Chapter 1. The Cognitive Sciences: One or Many? | 1 1.0 Chapter Overview | 1 1.1 A Fragmented Psychology | 2 1.2 A Unified Cognitive Science | 3 1.3 Cognitive Science or the Cognitive Sciences? | 6 1.4 Cognitive Science: Pre-paradigmatic? | 13 1.5 A Plan of Action | 16 Chapter 2. Multiple Levels of Investigation | 19 2.0 Chapter Overview | 19 2.1 Machines and Minds | 20 2.2 From the Laws of Thought to Binary Logic | 23 2.3 From the Formal to the Physical | 29 2.4 Multiple Procedures and Architectures | 32 2.5 Relays and Multiple Realizations | 35 2.6 Multiple Levels of Investigation and Explanation | 38 2.7 Formal Accounts of Input-Output Mappings | 40 2.8 Behaviour by Design and by Artifact | 41 2.9 Algorithms from Artifacts | 43 2.10 Architectures against Homunculi | 46 2.11 Implementing Architectures | 48 2.12 Levelling the Field | 51 Chapter 3. Elements of Classical Cognitive Science | 55 3.0 Chapter Overview | 55 3.1 Mind, Disembodied | 56 3.2 Mechanizing the Infinite | 59 3.3 Phrase Markers and Fractals | 65 3.4 Behaviourism, Language, and Recursion | 68 3.5 Underdetermination and Innateness | 72 3.6 Physical Symbol Systems | 75 3.7 Componentiality, Computability, and Cognition | 78 3.8 The Intentional Stance | 82 3.9 Structure and Process | 85 3.10 A Classical Architecture for Cognition | 89 3.11 Weak Equivalence and the Turing Test | 93 3.12 Towards Strong Equivalence | 97 3.13 The Impenetrable Architecture | 106 3.14 Modularity of Mind | 113 3.15 Reverse Engineering | 119 3.16 What is Classical Cognitive Science? | 122 Chapter 4. Elements of Connectionist Cognitive Science | 125 4.0 Chapter Overview | 125 4.1 Nurture versus Nature | 126 4.2 Associations | 133 4.3 Nonlinear Transformations | 139 4.4 The Connectionist Sandwich | 142 4.5 Connectionist Computations: An Overview | 148 4.6 Beyond the Terminal Meta-postulate | 149 4.7 What Do Output Unit Activities Represent? | 152 4.8 Connectionist Algorithms: An Overview | 158 4.9 Empiricism and Internal Representations | 159 4.10 Chord Classification by a Multilayer Perceptron | 162 4.11 Trigger Features | 172 4.12 A Parallel Distributed Production System | 177 4.13 Of Coarse Codes | 184 4.14 Architectural Connectionism: An Overview | 188 4.15 New Powers of Old Networks | 189 4.16 Connectionist Reorientation | 193 4.17 Perceptrons and Jazz Progressions | 195 4.18 What Is Connectionist Cognitive Science? | 198 Chapter 5. Elements of Embodied Cognitive Science | 205 5.0 Chapter Overview | 205 5.1 Abandoning Methodological Solipsism | 206 5.2 Societal Computing | 210 5.3 Stigmergy and Superorganisms | 212 5.4 Embodiment, Situatedness, and Feedback | 216 5.5 Umwelten, Affordances, and Enactive Perception | 219 5.6 Horizontal Layers of Control | 222 5.7 Mind in Action | 224 5.8 The Extended Mind | 230 5.9 The Roots of Forward Engineering | 235 5.10 Reorientation without Representation | 239 5.11 Robotic Moments in Social Environments | 245 5.12 The Architecture of Mind Reading | 250 5.13 Levels of Embodied Cognitive Science | 255 5.14 What Is Embodied Cognitive Science? | 260 Chapter 6. Classical Music and Cognitive Science | 265 6.0 Chapter Overview | 265 6.1 The Classical Nature of Classical Music | 266 6.2 The Classical Approach to Musical Cognition | 273 6.3 Musical Romanticism and Connectionism | 280 6.4 The Connectionist Approach to Musical Cognition | 286 6.5 The Embodied Nature of Modern Music | 291 6.6 The Embodied Approach to Musical Cognition | 301 6.7 Cognitive Science and Classical Music | 307 Chapter 7. Marks of the Classical? | 315 7.0 Chapter Overview | 315 7.1 Symbols and Situations | 316 7.2 Marks of the Classical | 324 7.3 Centralized versus Decentralized Control | 326 7.4 Serial versus Parallel Processing | 334 7.5 Local versus Distributed Representations | 339 7.6 Internal Representations | 343 7.7 Explicit Rules versus Implicit Knowledge | 345 7.8 The Cognitive Vocabulary | 348 7.9 From Classical Marks to Hybrid Theories | 355 Chapter 8. Seeing and Visualizing | 359 8.0 Chapter Overview | 359 8.1 The Transparency of Visual Processing | 360 8.2 The Poverty of the Stimulus | 362 8.3 Enrichment via Unconscious Inference | 368 8.4 Natural Constraints | 371 8.5 Vision, Cognition, and Visual Cognition | 379 8.6 Indexing Objects in the World | 383
£33.15
Springer Nature Switzerland AG Mathematical Foundations of Advanced Informatics: Volume 1: Inductive Approaches
Book SynopsisThe books in this trilogy capture the foundational core of advanced informatics. The authors make the foundations accessible, enabling students to become effective problem solvers.This first volume establishes the inductive approach as a fundamental principle for system and domain analysis. After a brief introduction to the elementary mathematical structures, such as sets, propositional logic, relations, and functions, the authors focus on the separation between syntax (representation) and semantics (meaning), and on the advantages of the consistent and persistent use of inductive definitions. They identify compositionality as a feature that not only acts as a foundation for algebraic proofs but also as a key for more general scalability of modeling and analysis. A core principle throughout is invariance, which the authors consider a key for the mastery of change, whether in the form of extensions, transformations, or abstractions.This textbook is suitable for undergraduate and graduate courses in computer science and for self-study. Most chapters contain exercises and the content has been class-tested over many years in various universities.Table of ContentsIntroduction.- Propositions and Sets.- Relations and Functions.- Inductive Definitions.- Inductive Proofs.- Inductive Approach: Potential, Limitations, and Pragmatics.
£27.99
Springer Nature Switzerland AG Tools and Algorithms for the Construction and Analysis of Systems: 25 Years of TACAS: TOOLympics, Held as Part of ETAPS 2019, Prague, Czech Republic, April 6–11, 2019, Proceedings, Part III
Book SynopsisThis book is Open Access under a CC BY licence. This book, LNCS 11429, is part III of the proceedings of the 25th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2019, which took place in Prague, Czech Republic, in April 2019, held as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2019. It's a special volume on the occasion of the 25 year anniversary of TACAS. Table of ContentsTOOLympics 2019: An Overview of Competitions in Formal Methods.- Confluence Competion 2019.- International Competition on Runtime Verification (CRV).- The Model Checking Contest (2019).- The 2019 Comparison of Tools for the Analysis of Quantitative Formal Models.- The Rewrite Engines Competitions: A RECtrospective.- RERS 2019: Combining Synthesis with Real-World Models.- SL-COMP: Competition of Solvers for Separation Logic.- Automatic Verification of C and Java Programs: SV-COMP 2019.- The Termination and Complexity Competition.- Competition on Software Testing (Test-Comp).- VerifyThis - Verification Competition with a Human Factor.- SV-COMP 2019.- CBMC Path: A Symbolic Execution Retrofit of the C Bounded Model Checker (Competition Contribution).- Extending DIVINE with Symbolic Verification using SMT (Competition Contribution).- ESBMC v6.0: Verifying C Programs using k-Induction and Invariant Inference (Competition Contribution).- JBMC: Bounded Model Checking for Java Bytecode (Competition Contribution).- JayHorn: A Java Model Checker (Competition Contribution).- Java Pathfinder at SV-COMP 2019.- Pinaka: Symbolic Execution meets Incremental Solving (Competition Contribution).- PeSCo: Predicting Sequential Combinations of Verifiers (Competition Contribution).- Symbolic Pathfinder for SV-COMP.- VeriFuzz: Program Aware Fuzzing.- VIAP 1.1 (Competition Contribution).
£40.49
Springer Nature Switzerland AG Unconventional Computation and Natural Computation: 18th International Conference, UCNC 2019, Tokyo, Japan, June 3–7, 2019, Proceedings
Book SynopsisThis book constitutes the proceedings of the 18th International Conference on Unconventional Computation and Natural Computation, UCNC 2019, held in Tokyo, Japan, in June 2019.The 19 full papers presented were carefully reviewed and selected from 32 submissions. The papers cover topics such as hypercomputation; chaos and dynamical systems based computing; granular, fuzzy and rough computing; mechanical computing; cellular, evolutionary, molecular, neural, and quantum computing; membrane computing; amorphous computing, swarm intelligence; artificial immune systems; physics of computation; chemical computation; evolving hardware; the computational nature of self-assembly, developmental processes, bacterial communication, and brain processes.Table of ContentsInvited Paper.- Co-designing the computational model and the computing substrate.- Contributed Papers.- Generalized Membrane Systems with Dynamical Structure, Petri Nets, and Multiset Approximation Spaces.- Quantum Dual Adversary for Hidden Subgroups and Beyond.- Further Properties of Self-assembly by Hairpin Formation.- The Role of Structure and Complexity on Reservoir Computing Quality.- Lindenmayer Systems and Global Transformations.- Swarm-based multiset rewriting computing models.- DNA Origami Words and Rewriting Systems.- Computational Limitations of Affine Automata.- An Exponentially Growing Nubot System Without State Changes.- Impossibility of Sufficiently Simple Chemical Reaction Network Implementations in DNA Strand Displacement.- Quantum Algorithm for Dynamic Programming Approach for DAGs. Applications for Zhegalkin Polynomial Evaluation and Some Problems on DAGs.- Viewing rate-based neurons as biophysical conductance outputting models.- The Lyapunov Exponents of Reversible Cellular Automata Are Uncomputable.- Geometric Tiles and Powers and Limitations of Geometric Hindrance in Self-Assembly.- DNA Computing Units Based on Fractional Coding.- The role of the representational entity in physical computing.- OIM: Oscillator-based Ising Machines for Solving Combinatorial Optimisation Problems.- Relativizations of Nonuniform Quantum Finite Automata Families.- Self-stabilizing Gellular Automata.
£44.99
Springer Nature Switzerland AG Theory of Information and its Value
Book SynopsisThis English version of Ruslan L. Stratonovich’s Theory of Information (1975) builds on theory and provides methods, techniques, and concepts toward utilizing critical applications. Unifying theories of information, optimization, and statistical physics, the value of information theory has gained recognition in data science, machine learning, and artificial intelligence. With the emergence of a data-driven economy, progress in machine learning, artificial intelligence algorithms, and increased computational resources, the need for comprehending information is essential. This book is even more relevant today than when it was first published in 1975. It extends the classic work of R.L. Stratonovich, one of the original developers of the symmetrized version of stochastic calculus and filtering theory, to name just two topics.Each chapter begins with basic, fundamental ideas, supported by clear examples; the material then advances to great detail and depth. The reader is not required to be familiar with the more difficult and specific material. Rather, the treasure trove of examples of stochastic processes and problems makes this book accessible to a wide readership of researchers, postgraduates, and undergraduate students in mathematics, engineering, physics and computer science who are specializing in information theory, data analysis, or machine learning.Trade Review“The book could be useful in advanced graduate courses with students, who are not afraid of integrals and probabilities.” (Jaak Henno, zbMATH 1454.94002, 2021)Table of Contents
£89.99
Springer Nature Switzerland AG Digital Libraries for Open Knowledge: 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, Oslo, Norway, September 9-12, 2019, Proceedings
Book SynopsisThis book constitutes the proceedings of the 23rd International Conference on Theory and Practice of Digital Libraries, TPDL 2019, held in Olslo, Norway, in September 2019. The 16 revised full papers,12 short papers and 18 poster papers presented were carefully reviewed and selected from 75 submissions. The general theme of TPDL 2019 was Connecting with Communities and so the papers attempt to facilitate establishing connections and convergences between diverse research communities such as Digital Humanities, Information Sciences and others that could benefit from ecosystems offered by digital libraries and repositories. To become especially useful to the diverse research and practitioner communities digital libraries need to consider special needs and requirements for effective data utilization, management and exploitation.Table of ContentsConer: A Collaborative Approach for Long-Tail Named Entity Recognition in Scientific Publications.- An unsupervised method for concept association analysis in text collections.- Linking Semantic Fingerprints of Literature.- Learning to Rank Claim-Evidence Pairs to Assist Scientific-Based Argumentation.- The OpenAIRE Research Community Dashboard: on Blending Scientific Workows and Scientific Publishing.- A Framework for Citing Nanopublications.- Analysis of Transaction Logs from National Museums Liverpool.- Knowledge Graph Implementation of Archival Descriptions through CIDOC-CRM.- Investigating Correlations of Inter-coder Agreement and Machine Annotation Performance for Historical Video Data.- Who is Mona L.? Identifying Mentions of Artworks in Historical Archives.- Gatekeeper: Quantifying the Impacts of Service to the Scientific Community.- A Study on the Readability of Scientific Publications.- Interdisciplinary Collaborations in the Brazilian Scientific Community.- Exploring Scholarly Data by Semantic Query on Knowledge Graph Embedding Space.- The Memento Tracer Framework: Balancing Quality and Scalability for Web Archiving.- The immigration dilemma; Legal, ethical and practical issues in creating a living, growing archive.- Segmenting User Sessions in Search Engine Query Logs Leveraging Word Embeddings.- A Human-friendly Query Generation Frontend for a Scientific Events Knowledge Graph.- User Interface for Interactive Scientific Publications: A Design Case Study.- Stable Word-clouds for Visualising Text-changes over Time.- A Hierarchical Label Network for Multi-Label EuroVoc Classification of Legislative Contents.- Can Language Inference Support Metadata Generation?.- Information Governance Maturity Assessment using Enterprise Architecture Model Analysis and Description Logics.- Finding Documents Related to Taiwan in the Veritable Records of Qing Using Relevance Feedback.- Fake News Detection with the New German Dataset "GermanFakeNC".- The CSO Classifier: Ontology-Driven Detection of Research Topics in Scholarly Articles.- Non-parametric Subject Prediction.- Visual Summarization of Scholarly Videos using Word Embeddings and Keyphrase Extraction.- Towards Serendipitous Research Paper Recommender using Tweets and Diversification.- Enriching the Cultural Heritage Metadata Using Historical Events: a Graph-Based Representation.- Open Research Knowledge Graph: A System Walkthrough.- The Biodiversity Heritage Library: Unveiling a World of Knowledge About Life on Earth.- Clipping the Page { Automatic Article Detection and Marking Software in Production of Newspaper Clippings in a Digitized Historical Journalistic Collection.- Document recommendations in Slovenian academic digital libraries.- An Evaluation of the Effect of Reference Strings and Segmentation on Citation Matching.- A la Carte: Turning Historical Menu into Menu Network.- Semantic Representation of Scientific Publications.- Determining How Citations Are Used in Citation Contexts.- Dendro: a FAIR, open-source data sharing platform.- User's Behavior in Digital Libraries: Process Mining Exploration.- SciTo Trends: Visualising Scientific Topic Trends.- The-Shelf Semantic Author Name Disambiguation for Bibliographic Data Bases.- Rending Behaviour in Educational Search.- Qatar Digital Library as a Platform for Digital Repatriation of Qatar's Cultural Heritage.- Correcting and redesigning metadata for the excavation of an archaeological site.- Topic Modelling vs Distant Supervision: A Comparative Evaluation based on the Classification of Parliamentary Enquiries.
£58.49
Springer Nature Switzerland AG Deep Learning Architectures: A Mathematical
Book SynopsisThis book describes how neural networks operate from the mathematical point of view. As a result, neural networks can be interpreted both as function universal approximators and information processors. The book bridges the gap between ideas and concepts of neural networks, which are used nowadays at an intuitive level, and the precise modern mathematical language, presenting the best practices of the former and enjoying the robustness and elegance of the latter.This book can be used in a graduate course in deep learning, with the first few parts being accessible to senior undergraduates. In addition, the book will be of wide interest to machine learning researchers who are interested in a theoretical understanding of the subject. Trade Review“This book is useful to students who have already had an introductory course in machine learning and are further interested to deepen their understanding of the machine learning material from the mathematical point of view.” (T. C. Mohan, zbMATH 1441.68001, 2020)Table of ContentsIntroductory Problems.- Activation Functions.- Cost Functions.- Finding Minima Algorithms.- Abstract Neurons.- Neural Networks.- Approximation Theorems.- Learning with One-dimensional Inputs.- Universal Approximators.- Exact Learning.- Information Representation.- Information Capacity Assessment.- Output Manifolds.- Neuromanifolds.- Pooling.- Convolutional Networks.- Recurrent Neural Networks.- Classification.- Generative Models.- Stochastic Networks.- Hints and Solutions.
£71.99
Springer Nature Switzerland AG Will We Ever Have a Quantum Computer?
Book SynopsisThis book addresses a broad community of physicists, engineers, computer scientists and industry professionals, as well as the general public, who are aware of the unprecedented media hype surrounding the supposedly imminent new era of quantum computing. The central argument of this book is that the feasibility of quantum computing in the physical world is extremely doubtful. The hypothetical quantum computer is not simply a quantum variant of the conventional digital computer, but rather a quantum extension of a classical analog computer operating with continuous parameters. In order to have a useful machine, the number of continuous parameters to control would have to be of such an astronomically large magnitude as to render the endeavor virtually infeasible. This viewpoint is based on the author’s expert understanding of the gargantuan challenges that would have to be overcome to ever make quantum computing a reality. Knowledge of secondary-school-level physics and math will be sufficient for understanding most of the text.Table of ContentsIntroduction.- Brief history of quantum computing, starting with the invention of Shor's algorithm (1994).- Introduction to quantum mechanics for pedestrians.- Electron spin as a qubit.- The main ideas and promises of quantum computing.- Current state of the art.
£52.24
Springer Nature Switzerland AG Graph Transformation for Software Engineers: With
Book SynopsisThis book is an introduction to graph transformation as a foundation to model-based software engineering at the level of both individual systems and domain-specific modelling languages.The first part of the book presents the fundamentals in a precise, yet largely informal way. Besides serving as prerequisite for describing the applications in the second part, it also provides a comprehensive and systematic survey of the concepts, notations and techniques of graph transformation. The second part presents and discusses a range of applications to both model-based software engineering and domain-specific language engineering. The variety of these applications demonstrates how broadly graphs and graph transformations can be used to model, analyse and implement complex software systems and languages. This is the first textbook that explains the most commonly used concepts, notations, techniques and applications of graph transformation without focusing on one particular mathematical representation or implementation approach. Emphasising the research and engineering methodologies used, it will be a valuable resource for graduate students, practitioners and researchers in software engineering, foundations of programming and formal methods.Table of ContentsPart I, Graph Transformation.- Graphs for Modeling and Specification.- Graph Transformation Concepts.- Beyond Individual Rules: Usage Scenarios and Control Structures.- Analysis and Improvement of Graph Transformation Systems.- Part II, Graph Transformation in Software Engineering.- Detecting Inconsistent Requirements in a Use Case-Driven Approach.- Service Specification and Matching.- Model-Based Testing.- Reverse Engineering: Inferring Visual Contracts from Java Programs.- Stochastic Analysis of Dynamic Software Architectures.- Advanced Modeling Language Definition: Integrating Meta-modeling with Graph Transformation.- Improving Models and Understanding Model Changes.- Translating and Synchronizing Models.
£75.99
Springer Nature Switzerland AG Quantum Computing for the Quantum Curious
Book SynopsisThis open access book makes quantum computing more accessible than ever before. A fast-growing field at the intersection of physics and computer science, quantum computing promises to have revolutionary capabilities far surpassing “classical” computation. Getting a grip on the science behind the hype can be tough: at its heart lies quantum mechanics, whose enigmatic concepts can be imposing for the novice. This classroom-tested textbook uses simple language, minimal math, and plenty of examples to explain the three key principles behind quantum computers: superposition, quantum measurement, and entanglement. It then goes on to explain how this quantum world opens up a whole new paradigm of computing. The book bridges the gap between popular science articles and advanced textbooks by making key ideas accessible with just high school physics as a prerequisite. Each unit is broken down into sections labelled by difficulty level, allowing the course to be tailored to the student’s experience of math and abstract reasoning. Problem sets and simulation-based labs of various levels reinforce the concepts described in the text and give the reader hands-on experience running quantum programs. This book can thus be used at the high school level after the AP or IB exams, in an extracurricular club, or as an independent project resource to give students a taste of what quantum computing is really about. At the college level, it can be used as a supplementary text to enhance a variety of courses in science and computing, or as a self-study guide for students who want to get ahead. Additionally, readers in business, finance, or industry will find it a quick and useful primer on the science behind computing’s future. Table of ContentsContents.- 1 Introduction to Superposition.- 2 What is a Qubit?.- 3 Creating Superposition: The Beam Splitter.- 4 Creating Superposition: Stern-Gerlach.- 5 Quantum Cryptography.- 6 Quantum Gates.- 7 Entanglement.- 8 Quantum Teleportation.- 9 Quantum Algorithms.- 10 Worksheets.- Appendices.- Alphabetical Index.- Acknowledgments.- Answers.
£34.99
Springer Nature Switzerland AG Modelling Puzzles in First Order Logic
Book SynopsisKeeping students involved and actively learning is challenging. Instructors in computer science are aware of the cognitive value of modelling puzzles and often use logical puzzles as an efficient pedagogical instrument to engage students and develop problem-solving skills. This unique book is a comprehensive resource that offers teachers and students fun activities to teach and learn logic. It provides new, complete, and running formalisation in Propositional and First Order Logic for over 130 logical puzzles, including Sudoku-like puzzles, zebra-like puzzles, island of truth, lady and tigers, grid puzzles, strange numbers, or self-reference puzzles. Solving puzzles with theorem provers can be an effective cognitive incentive to motivate students to learn logic. They will find a ready-to-use format which illustrates how to model each puzzle, provides running implementations, and explains each solution. This concise and easy-to-follow textbook is a much-needed support tool for students willing to explore beyond the introductory level of learning logic and lecturers looking for examples to heighten student engagement in their computer science courses. Trade Review“The purpose of this book is to introduce first-order logic (FOL) to newcomers. … The book is a treasure trove of puzzles like this. … All of these are motivated in an approachable, fun way. … the book is a hands-on guide to Prover9 and Mace4 … . It is quite valuable to have so many puzzles in a single book.” (Jesse Adam Alama, Mathematical Reviews, October, 2022)Table of ContentsPreface.- Getting Started with Prover9 and Mace4.- Micro Arithmetic Puzzles.- Strange Numbers.- Practical Puzzles.- Lady and Tigers.- Einstein Puzzles.- Island of Truth.- Love and Marriage.- Grid Puzzles.- Japanese Puzzles.- Russian Puzzles.- Polyomino Puzzles.- Self-reference and Other Puzzles.- Epigraph in Natural Language
£40.49
Springer Nature Switzerland AG Fundamentals of Quantum Computing: Theory and
Book SynopsisThis introductory book on quantum computing includes an emphasis on the development of algorithms. Appropriate for both university students as well as software developers interested in programming a quantum computer, this practical approach to modern quantum computing takes the reader through the required background and up to the latest developments. Beginning with introductory chapters on the required math and quantum mechanics, Fundamentals of Quantum Computing proceeds to describe four leading qubit modalities and explains the core principles of quantum computing in detail. Providing a step-by-step derivation of math and source code, some of the well-known quantum algorithms are explained in simple ways so the reader can try them either on IBM Q or Microsoft QDK. The book also includes a chapter on adiabatic quantum computing and modern concepts such as topological quantum computing and surface codes.Features:o Foundational chapters that build the necessary background on math and quantum mechanics.o Examples and illustrations throughout provide a practical approach to quantum programming with end-of-chapter exercises.o Detailed treatment on four leading qubit modalities -- trapped-ion, superconducting transmons, topological qubits, and quantum dots -- teaches how qubits work so that readers can understand how quantum computers work under the hood and devise efficient algorithms and error correction codes. Also introduces protected qubits - 0-π qubits, fluxon parity protected qubits, and charge-parity protected qubits. o Principles of quantum computing, such as quantum superposition principle, quantum entanglement, quantum teleportation, no-cloning theorem, quantum parallelism, and quantum interference are explained in detail. A dedicated chapter on quantum algorithm explores both oracle-based, and Quantum Fourier Transform-based algorithms in detail with step-by-step math and working code that runs on IBM QisKit and Microsoft QDK. Topics on EPR Paradox, Quantum Key Distribution protocols, Density Matrix formalism, and Stabilizer formalism are intriguing. While focusing on the universal gate model of quantum computing, this book also introduces adiabatic quantum computing and quantum annealing.This book includes a section on fault-tolerant quantum computing to make the discussions complete. The topics on Quantum Error Correction, Surface codes such as Toric code and Planar code, and protected qubits help explain how fault tolerance can be built at the system level.Trade Review“The book represents a new and fresh approach to quantum computing, starting with theoretical physical knowledge that is highlighted by beautiful figures. Then, quantum computing is explained by quantum programing languages and extensive languages. It is recommended to everyone interested in quantum computing. It is easy to follow through a beautiful and clear presentation, programming examples and additional exercises.” (Andreas Wichert, zbMATH 1477.68005, 2022)Table of ContentsPART ONE 1 Foundations of Quantum Mechanics 1.1 Matter 1.2 Atoms, Elementary Particles, and Molecules 1.3 Light and Quantization of Energy 1.4 Electron Configuration 1.5 Wave-Particle Duality and Probabilistic Nature 1.6 Wavefunctions and Probability Amplitudes 1.7 Some exotic states of matter 1.8 Summary 1.9 Practice Problems 1.10 References and further reading 2 Dirac’s bra-ket notation and Hermitian Operators2.1 Scalars 2.2 Complex Numbers 2.3 Vectors 2.4 Matrices 2.5 Linear Vector Spaces 2.6 Using Dirac’s bra-ket notation 2.7 Expectation Values and Variances2.8 Eigenstates, Eigenvalues and Eigenfunctions2.9 Characteristic Polynomial 2.10 Definite Symmetric Matrices 2.11 Tensors2.12 Statistics and Probability2.13 Summary 2.14 Practice problems2.15 References and further reading3 The Quantum Superposition Principle and Bloch Sphere Representation3.1 Euclidian Space3.2 Metric Space3.3 Hilbert space.3.4 Schrodinger Equation3.5 Postulates of Quantum Mechanics3.6 Quantum Tunneling3.7 Stern and Gerlach Experiment3.8 Bloch sphere representation3.9 Projective Measurements3.10 Qudits3.11 Summary3.12 Practice Problems3.13 References and further readingPART TWO4 Qubit Modalities4.1 The vocabulary of quantum computing4.2 Classical Computers – a recap 4.3 Qubits and usability4.4 Noisy Intermediate Scale Quantum Technology4.5 Qubit Metrics4.6 Leading Qubit Modalities4.7 A note on the dilution refrigerator4.8 Summary4.9 Practice Problems4.10 References and further reading5 Quantum Circuits and DiVincenzo Criteria5.1 Setting up the development environment5.2 Learning Quantum Programming Languages 5.3 Introducing Quantum Circuits 5.4 Quantum Gates 5.5 The Compute Stage5.6 Quantum Entanglement5.7 No-Cloning theorem5.8 Quantum Teleportation5.9 Superdense coding5.10 Greenberger–Horne–Zeilinger state (GHZ state)5.11 Walsh-Hadamard Transform5.12 Quantum Interference5.13 Phase kickback5.14 DiVincenzo’s criteria for quantum computation5.15 Summary 5.16 Practice Problems5.17 References and further reading6 Quantum Communications6.1 EPR Paradox6.2 Density Matrix Formalism6.3 Von Neumann Entropy6.4 Photons6.5 Quantum Communication6.6 The Quantum Channel6.7 Quantum Communication Protocols6.8 RSA Security6.9 Summary6.10 Practice Problems6.11 References and further reading7 Quantum Algorithms7.1 Quantum Ripple Adder Circuit7.2 Quantum Fourier Transformation7.3 Deutsch-Jozsa oracle7.4 The Bernstein-Vazirani Oracle7.5 Simon’s algorithm7.6 Quantum arithmetic using QFT7.7 Modular exponentiation7.8 Grover’s search algorithm 7.9 Shor’s algorithm7.10 A quantum algorithm for k-means7.11 Quantum Phase Estimation (QPE)7.12 HHL algorithm for solving linear equations7.13 Quantum Complexity Theory7.14 Summary 7.15 Practice Problems7.16 References and further reading8 Adiabatic Optimization and Quantum Annealing8.1 Adiabatic evolution8.2 Proof of the Adiabatic Theorem8.3 Adiabatic optimization8.4 Quantum Annealing8.5 Summary8.6 Practice Problems8.7 References and further reading9 Quantum Error Correction9.1 Classical Error Correction9.2 Quantum Error Codes9.3 Stabilizer formalism9.4 The path forward – fault-tolerant quantum computing9.5 Surface codes9.6 Protected qubits9.7 Practice Problems9.8 References and further reading10 Conclusion10.1 How many qubits do we need?10.2 Classical simulation10.3 Backends today10.4 Future state10.5 References
£75.99
Springer Nature Switzerland AG Lessons in Enumerative Combinatorics
Book SynopsisThis textbook introduces enumerative combinatorics through the framework of formal languages and bijections. By starting with elementary operations on words and languages, the authors paint an insightful, unified picture for readers entering the field. Numerous concrete examples and illustrative metaphors motivate the theory throughout, while the overall approach illuminates the important connections between discrete mathematics and theoretical computer science. Beginning with the basics of formal languages, the first chapter quickly establishes a common setting for modeling and counting classical combinatorial objects and constructing bijective proofs. From here, topics are modular and offer substantial flexibility when designing a course. Chapters on generating functions and partitions build further fundamental tools for enumeration and include applications such as a combinatorial proof of the Lagrange inversion formula. Connections to linear algebra emerge in chapters studying Cayley trees, determinantal formulas, and the combinatorics that lie behind the classical Cayley–Hamilton theorem. The remaining chapters range across the Inclusion-Exclusion Principle, graph theory and coloring, exponential structures, matching and distinct representatives, with each topic opening many doors to further study. Generous exercise sets complement all chapters, and miscellaneous sections explore additional applications. Lessons in Enumerative Combinatorics captures the authors' distinctive style and flair for introducing newcomers to combinatorics. The conversational yet rigorous presentation suits students in mathematics and computer science at the graduate, or advanced undergraduate level. Knowledge of single-variable calculus and the basics of discrete mathematics is assumed; familiarity with linear algebra will enhance the study of certain chapters.Trade Review“The wide variety of slightly unusual topics makes the book an excellent resource for the instructor who wants to craft a combinatorics course that contains a diverse collection of attractive results … . The attentive student will certainly come away from a course based on this book with a solid understanding of the combinatorial way of thinking. … the book is an excellent resource for anyone teaching a class in combinatorics.” (Timothy Y. Chow, Mathematical Reviews, March, 2023)“A whole book whose backbone is enumeration by codifying the objects to be enumerated as words. … They do this in a skillfully structured fashion which makes the connections natural and unforced. … One of the remarkable features of this book is the care the authors have taken to make it reader-friendly and accessible to a wide range of students following a graduate mathematics course or an honours undergraduate course in mathematics and computer science.” (Josef Lauri, zbMATH 1478.05001, 2022)Table of Contents1. Basic Combinatorial Structures.- 2. Partitions and Generating Functions.- 3. Planar Trees and the Lagrange Inversion Formula.- 4. Cayley Trees.- 5. The Cayley–Hamilton Theorem.- 6. Exponential Structures and Polynomial Operators.- 7. The Inclusion-Exclusion Principle.- 8. Graphs, Chromatic Polynomials and Acyclic Orientations.- 9. Matching and Distinct Representatives.
£52.24
Springer Nature Switzerland AG Lessons in Enumerative Combinatorics
Book SynopsisThis textbook introduces enumerative combinatorics through the framework of formal languages and bijections. By starting with elementary operations on words and languages, the authors paint an insightful, unified picture for readers entering the field. Numerous concrete examples and illustrative metaphors motivate the theory throughout, while the overall approach illuminates the important connections between discrete mathematics and theoretical computer science. Beginning with the basics of formal languages, the first chapter quickly establishes a common setting for modeling and counting classical combinatorial objects and constructing bijective proofs. From here, topics are modular and offer substantial flexibility when designing a course. Chapters on generating functions and partitions build further fundamental tools for enumeration and include applications such as a combinatorial proof of the Lagrange inversion formula. Connections to linear algebra emerge in chapters studying Cayley trees, determinantal formulas, and the combinatorics that lie behind the classical Cayley–Hamilton theorem. The remaining chapters range across the Inclusion-Exclusion Principle, graph theory and coloring, exponential structures, matching and distinct representatives, with each topic opening many doors to further study. Generous exercise sets complement all chapters, and miscellaneous sections explore additional applications. Lessons in Enumerative Combinatorics captures the authors' distinctive style and flair for introducing newcomers to combinatorics. The conversational yet rigorous presentation suits students in mathematics and computer science at the graduate, or advanced undergraduate level. Knowledge of single-variable calculus and the basics of discrete mathematics is assumed; familiarity with linear algebra will enhance the study of certain chapters.Trade Review“The wide variety of slightly unusual topics makes the book an excellent resource for the instructor who wants to craft a combinatorics course that contains a diverse collection of attractive results … . The attentive student will certainly come away from a course based on this book with a solid understanding of the combinatorial way of thinking. … the book is an excellent resource for anyone teaching a class in combinatorics.” (Timothy Y. Chow, Mathematical Reviews, March, 2023)“A whole book whose backbone is enumeration by codifying the objects to be enumerated as words. … They do this in a skillfully structured fashion which makes the connections natural and unforced. … One of the remarkable features of this book is the care the authors have taken to make it reader-friendly and accessible to a wide range of students following a graduate mathematics course or an honours undergraduate course in mathematics and computer science.” (Josef Lauri, zbMATH 1478.05001, 2022)Table of Contents1. Basic Combinatorial Structures.- 2. Partitions and Generating Functions.- 3. Planar Trees and the Lagrange Inversion Formula.- 4. Cayley Trees.- 5. The Cayley–Hamilton Theorem.- 6. Exponential Structures and Polynomial Operators.- 7. The Inclusion-Exclusion Principle.- 8. Graphs, Chromatic Polynomials and Acyclic Orientations.- 9. Matching and Distinct Representatives.
£42.74
Springer Nature Switzerland AG Constructive Fractional Analysis with
Book SynopsisThis book includes constructive approximation theory; it presents ordinary and fractional approximations by positive sublinear operators, and high order approximation by multivariate generalized Picard, Gauss–Weierstrass, Poisson–Cauchy and trigonometric singular integrals. Constructive and Computational Fractional Analysis recently is more and more in the center of mathematics because of their great applications in the real world. In this book, all presented is original work by the author given at a very general level to cover a maximum number of cases in various applications. The author applies generalized fractional differentiation techniques of Riemann–Liouville, Caputo and Canavati types and of fractional variable order to various kinds of inequalities such as of Opial, Hardy, Hilbert–Pachpatte and on the spherical shell. He continues with E. R. Love left- and right-side fractional integral inequalities. They follow fractional Landau inequalities, of left and right sides, univariate and multivariate, including ones for Semigroups. These are developed to all possible directions, and right-side multivariate fractional Taylor formulae are proven for the purpose. It continues with several Gronwall fractional inequalities of variable order. This book results are expected to find applications in many areas of pure and applied mathematics. As such this book is suitable for researchers, graduate students and seminars of the above disciplines, also to be in all science and engineering libraries.Table of ContentsVariable order general fractional integral inequalitie.- Variable order fractional integral inequalities for spherical shell.- Left fractional integral inequalities of E.R. Love type.- Right side fractional integral inequalities of E.R. Love type.- General fractional Landau inequalities.- Abstract fractional Landau inequalities.- Fractional Landau inequalities of Riemann-Liouville type.- Generalized Canavati fractional Landau inequalities.- Sequential left abstract fractional Landau inequalities.- Iterated left abstract generalized fractional Landau inequalities.
£125.99
Springer Nature Switzerland AG Tools and Algorithms for the Construction and Analysis of Systems: 27th International Conference, TACAS 2021, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2021, Luxembourg City, Luxembourg, March
Book SynopsisThis open access two-volume set constitutes the proceedings of the 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2021, which was held during March 27 – April 1, 2021, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2021. The conference was planned to take place in Luxembourg and changed to an online format due to the COVID-19 pandemic.The total of 41 full papers presented in the proceedings was carefully reviewed and selected from 141 submissions. The volume also contains 7 tool papers; 6 Tool Demo papers, 9 SV-Comp Competition Papers. The papers are organized in topical sections as follows: Part I: Game Theory; SMT Verification; Probabilities; Timed Systems; Neural Networks; Analysis of Network Communication. Part II: Verification Techniques (not SMT); Case Studies; Proof Generation/Validation; Tool Papers; Tool Demo Papers; SV-Comp Tool Competition Papers.Table of ContentsGame Theory.- A Game for Linear-time - Branching-time Spectroscopy.- On Satisficing in Quantitative Games.- Quasipolynomial Computation of Nested Fixpoints.- SMT Verification.- A Flexible Proof Format for SAT Solver-Elaborator Communication.- Generating Extended Resolution Proofs with a BDD-Based SAT Solver.- Bounded Model Checking for Hyperproperties.- Counterexample-Guided Prophecy for Model Checking Modulo the Theory of Arrays.- SAT Solving with GPU Accelerated Inprocessing.- FOREST: An Interactive Multi-tree Synthesizer for Regular Expressions.- Probabilities.- Finding Provably Optimal Markov Chains.- Inductive Synthesis for Probabilistic Programs Reaches New Horizons.- Analysis of Markov Jump Processes under Terminal Constraints.- Multi-objective Optimization of Long-run Average and Total Rewards.- Inferring Expected Runtimes of Probabilistic Integer Programs Using Expected Sizes.- Probabilistic and Systematic Coverage of Consecutive Test-Method Pairs for Detecting Order-Dependent Flaky Tests.- Timed Systems.- Timed Automata Relaxation for Reachability.- Iterative Bounded Synthesis for Efficient Cycle Detection in Parametric Timed Automata.- Algebraic Quantitative Semantics for Efficient Online Temporal Monitoring.- Neural Networks.- Synthesizing Context-free Grammars from Recurrent Neural Networks.- Automated and Formal Synthesis of Neural Barrier Certificates for Dynamical Models.- Improving Neural Network Verification through Spurious Region Guided Refinement.- Analysis of Network Communication Resilient Capacity-Aware Routing.- Network Traffic Classification by Program Synthesis.
£34.99
Springer Nature Switzerland AG Computational Diffusion MRI: International MICCAI
Book SynopsisThis book gathers papers presented at the Workshop on Computational Diffusion MRI, CDMRI 2020, held under the auspices of the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), which took place virtually on October 8th, 2020, having originally been planned to take place in Lima, Peru.This book presents the latest developments in the highly active and rapidly growing field of diffusion MRI. While offering new perspectives on the most recent research challenges in the field, the selected articles also provide a valuable starting point for anyone interested in learning computational techniques for diffusion MRI. The book includes rigorous mathematical derivations, a large number of rich, full-colour visualizations, and clinically relevant results. As such, it is of interest to researchers and practitioners in the fields of computer science, MRI physics, and applied mathematics. The reader will find numerous contributions covering a broad range of topics, from the mathematical foundations of the diffusion process and signal generation to new computational methods and estimation techniques for the in-vivo recovery of microstructural and connectivity features, as well as diffusion-relaxometry and frontline applications in research and clinical practice.Table of Contents
£143.99
Springer Nature Switzerland AG Domain Science and Engineering: A Foundation for
Book SynopsisIn this book the author explains domain engineering and the underlying science, and he then shows how we can derive requirements prescriptions for computing systems from domain descriptions. A further motivation is to present domain descriptions, requirements prescriptions, and software design specifications as mathematical quantities.The author's maxim is that before software can be designed we must understand its requirements, and before requirements can be prescribed we must analyse and describe the domain for which the software is intended. He does this by focusing on what it takes to analyse and describe domains. By a domain we understand a rationally describable discrete dynamics segment of human activity, of natural and man-made artefacts, examples include road, rail and air transport, container terminal ports, manufacturing, trade, healthcare, and urban planning. The book addresses issues of seemingly large systems, not small algorithms, and it emphasizes descriptions as formal, mathematical quantities.This is the first thorough monograph treatment of the new software engineering phase of software development, one that precedes requirements engineering. It emphasizes a methodological approach by treating, in depth, analysis and description principles, techniques and tools. It does this by basing its domain modeling on fundamental philosophical principles, a view that is new for a computer science monograph.The book will be of value to computer scientists engaged with formal specifications of software. The author reveals this as a field of interesting problems, most chapters include pointers to further study and exercises drawn from practical engineering and science challenges. The text is supported by a primer to the formal specification language RSL and extensive indexes.Table of ContentsPart I, Setting the Scope.- Concepts.- Philosophy.- Space, Time and Matter.- Logic and Mathematics.- Part II, Domains.- Domains: A Taxonomy: External Qualities.- Domains: An Ontology: Internal Qualities.- Transcendental Deduction.- Domains: A Dynamics Ontology: Perdurants.- Domain Facets.- Part III, Requirements.- Requirements.- Part IV, Closing.- Demos, Simulators, Monitors and Controllers.- Winding Up.- References.- Appendix A: Pipelines Domain: Endurants.- Appendix B: Mereology, A Model.- Appendix C: Four Languages.- Appendix D: An RSL Primer.- Appendix E: Indexes.- List of Figures
£125.99
Springer Nature Switzerland AG Algorithms and Complexity: 12th International Conference, CIAC 2021, Virtual Event, May 10–12, 2021, Proceedings
Book SynopsisThis book constitutes the refereed conference proceedings of the 12th International Conference on Algorithms and Complexity, CIAC 2019, held as a virtual event, in May 2021. The 28 full papers presented together with one invited lecture and 2 two abstracts of invited lectures were carefully reviewed and selected from 78 submissions. The International Conference on Algorithms and Complexity is intended to provide a forum for researchers working in all aspects of computational complexity and the use, design, analysis and experimentation of efficient algorithms and data structures. The papers present original research in the theory and applications of algorithms and computational complexity.Due to the Corona pandemic the conference was held virtually.Table of ContentsAbundant Extensions.- Three Problems on Well-Partitioned Chordal Graphs.- Distributed Distance-r Covering Problems on Sparse High-Girth Graphs.- Reconfiguration of Connected Graph Partitions via Recombination.- Algorithms for Energy Conservation in Heterogeneous Data Centers.- On Vertex-Weighted Graph Realizations.- On the Role of 3's for the 1-2-3 Conjecture.- Upper Tail Analysis of Bucket Sort and Random Tries.- Throughput Scheduling with Equal Additive Laxity.- Fragile Complexity of Adaptive Algorithms.- FPT and Kernelization Algorithms for the Induced Tree Problem.- A Tight Lower Bound for Edge-Disjoint Paths on Planar DAGs.- Upper Dominating Set: Tight Algorithms for Pathwidth and Sub-Exponential Approximation.- A Multistage View on 2-Satisfiability.- The Weisfeiler-Leman Algorithm and Recognition of Graph Properties.- The Parameterized Suffix Tray.- Exploring the Gap Between Treedepth and Vertex Cover Through Vertex Integrity.- Covering a Set of Line Segments with a Few Squares.- Circumventing Connectivity for Kernelization.- Online and Approximate Network Construction from Bounded Connectivity Constraints.- Globally Rigid Augmentation of Minimally Rigid Graphs in \(R^2\).- Extending Partial Representations of Rectangular Duals with Given Contact Orientations.- Can Local Optimality be Used for Efficient Data Reduction.- Colouring Graphs of Bounded Diameter in the Absence of Small Cycles.- Online Two-Dimensional Vector Packing with Advice.- Temporal Matching on Geometric Graph Data.
£61.74
Springer Nature Switzerland AG Advances in Knowledge Discovery and Data Mining: 25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11–14, 2021, Proceedings, Part III
Book SynopsisThe 3-volume set LNAI 12712-12714 constitutes the proceedings of the 25th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2021, which was held during May 11-14, 2021.The 157 papers included in the proceedings were carefully reviewed and selected from a total of 628 submissions. They were organized in topical sections as follows: Part I: Applications of knowledge discovery and data mining of specialized data; Part II: Classical data mining; data mining theory and principles; recommender systems; and text analytics; Part III: Representation learning and embedding, and learning from data.Table of ContentsRepresentation Learning and Embedding.- Episode Adaptive Embedding Networks for Few-shot Learning.- Universal Representation for Code.- Self-supervised Adaptive Aggregator Learning on Graph.- A Fast Algorithm for Simultaneous Sparse Approximation.- STEPs-RL: Speech-Text Entanglement for Phonetically Sound Representation Learning.- RW-GCN: Training Graph Convolution Networks with biased random walk for Semi-Supervised Classification.- Loss-aware Pattern Inference: A Correction on the Wrongly Claimed Limitations of Embedding Models.- SST-GNN: Simplified Spatio-temporal Traffic forecasting model using Graph Neural Network.- VIKING: Adversarial Attack on Network Embeddings via Supervised Network Poisoning.- Self-supervised Graph Representation Learning with Variational Inference.- Manifold Approximation and Projection by Maximizing Graph Information.- Learning Attention-based Translational Knowledge Graph Embedding via Nonlinear Dynamic Mapping.- Multi-Grained Dependency Graph Neural Network for Chinese Open Information Extraction.- Human-Understandable Decision Making for Visual Recognition.- LightCAKE: A Lightweight Framework for Context-Aware Knowledge Graph Embedding.- Transferring Domain Knowledge with an Adviser in Continuous Tasks.- Inferring Hierarchical Mixture Structures: A Bayesian Nonparametric Approach.- Quality Control for Hierarchical Classification with Incomplete Annotations.- Learning from Data.- Learning Discriminative Features using Multi-label Dual Space.- AutoCluster: Meta-learning Based Ensemble Method for Automated Unsupervised Clustering.- BanditRank: Learning to Rank Using Contextual Bandits.- A compressed and accelerated SegNet for plant leaf disease segmentation: A Differential Evolution based approach.- Meta-Context Transformers for Domain-Specific Response Generation.- A Multi-task Kernel Learning Algorithm for Survival Analysis.- Meta-data Augmentation based Search Strategy through Generative Adversarial Network for AutoML Model Selection.- Tree-Capsule: Tree-Structured Capsule Network for Improving Relation Extraction.- Rule Injection-based Generative Adversarial Imitation Learning for Knowledge Graph Reasoning.- Hierarchical Self Attention Based Autoencoder for Open-Set Human Activity Recognition.- Reinforced Natural Language Inference for Distantly Supervised Relation Classification.- SaGCN: Structure-aware Graph Convolution Network for Document-level Relation Extraction.- Addressing the class imbalance problem in medical image segmentation via accelerated Tversky loss function.- Incorporating Relational Knowledge in Explainable Fake News Detection.- Incorporating Syntactic Information into Relation Representations for Enhanced Relation Extraction.
£71.24
Springer Nature Switzerland AG Introduction to Computation: Haskell, Logic and
Book SynopsisComputation, itself a form of calculation, incorporates steps that include arithmetical and non-arithmetical (logical) steps following a specific set of rules (an algorithm). This uniquely accessible textbook introduces students using a very distinctive approach, quite rapidly leading them into essential topics with sufficient depth, yet in a highly intuitive manner. From core elements like sets, types, Venn diagrams and logic, to patterns of reasoning, calculus, recursion and expression trees, the book spans the breadth of key concepts and methods that will enable students to readily progress with their studies in Computer Science.Trade Review“This book is intended as a textbook for an introductory course in computation for students beginning in informatics. No prerequisites are needed, all concepts, even elementary ones ... . it is also very suited for self-study, even if a reader is interested in Haskell or symbolic logic alone. ... Comprehension is supported by exercises for each chapter ... .” (Dieter Riebesehl, zbMATH 1497.68005, 2022)Table of Contents1 Sets 132 Types 193 Simple Computations 274 Venn Diagrams and Logical Connectives 355 Lists and Comprehensions 456 Features and Predicates 557 Testing Your Programs 638 Patterns of Reasoning 739 More Patterns of Reasoning 8110 Lists and Recursion 9111 More Fun with Recursion 10112 Higher-Order Functions 11113 Higher and Higher 12314 Sequent Calculus 13115 Algebraic Data Types 14316 Expression Trees 15717 Karnaugh Maps 17518 Relations and Quantifiers 18319 Checking Satisfiability 19120 Data Representation 20321 Data Abstraction 22122 Efficient CNF Conversion 23723 Counting Satisfying Valuations 24924 Type Classes 26325 Search in Trees 27526 Combinatorial Algorithms 28527 Finite Automata 29928 Deterministic Finite Automata 31129 Non-Deterministic Finite Automata 32130 Input/Output and Monads 34131 Regular Expressions 35932 Non-Regular Languages 369Index 377
£28.49
Springer Nature Switzerland AG Multivariate Data Analysis on Matrix Manifolds:
Book SynopsisThis graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to be solved using (free) optimization software Manopt. The book includes numerous in-text examples as well as Manopt codes and software guides, which can be applied directly or used as templates for solving similar and new problems. The first two chapters provide an overview and essential background for studying MDA, giving basic information and notations. Next, it considers several sets of matrices routinely used in MDA as parameter spaces, along with their basic topological properties. A brief introduction to matrix (Riemannian) manifolds and optimization methods on them with Manopt complete the MDA prerequisite. The remaining chapters study individual MDA techniques in depth. The number of exercises complement the main text with additional information and occasionally involve open and/or challenging research questions. Suitable fields include computational statistics, data analysis, data mining and data science, as well as theoretical computer science, machine learning and optimization. It is assumed that the readers have some familiarity with MDA and some experience with matrix analysis, computing, and optimization. Table of ContentsIntroduction.- Matrix analysis and differentiation.- Matrix manifolds in MDA.- Principal component analysis (PCA).- Factor analysis (FA).- Procrustes analysis (PA).- Linear discriminant analysis (LDA).- Canonical correlation analysis (CCA).- Common principal components (CPC).- Metric multidimensional scaling (MDS) and related methods.- Data analysis on simplexes.
£40.49
Springer Nature Switzerland AG Arithmetic Geometry, Number Theory, and
Book SynopsisThis volume contains articles related to the work of the Simons Collaboration “Arithmetic Geometry, Number Theory, and Computation.” The papers present mathematical results and algorithms necessary for the development of large-scale databases like the L-functions and Modular Forms Database (LMFDB). The authors aim to develop systematic tools for analyzing Diophantine properties of curves, surfaces, and abelian varieties over number fields and finite fields. The articles also explore examples important for future research.Specific topics include● algebraic varieties over finite fields● the Chabauty-Coleman method● modular forms● rational points on curves of small genus● S-unit equations and integral points.Table of Contents A robust implementation for solving the S-unit equation and several application (C. Rasmussen).- Computing classical modular forms for arbitrary congruence subgroups (E. Assaf).- Square root time Coleman integration on superelliptic curves (A. Best).- Computing classical modular forms ( A. Sutherland).- Elliptic curves with good reduction outside of the first six primes (B. Matschke).- Efficient computation of BSD invariants in genus 2 (R. van Bommel).- Restrictions on Weil polynomials of Jacobians of hyperelliptic curves (E. Costa).- Zen and the art of database maintenance (D. Roe).- Effective obstructions to lifting Tate classes from positive characteristic (E. Costa).- Conjecture: 100% of elliptic surfaces over Q have rank zero (A. Cowan).- On rational Bianchi newforms and abelian surfaces with quaternionic multiplication (J. Voight).- A database of Hilbert modular forms (J. Voight).- Isogeny classes of Abelian Varieties over Finite Fields in the LMFDB (D. Roe).- Computing rational points on genus 3 hyperelliptic curves (S. Hashimoto).- Curves with sharp Chabauty-Coleman bound (S. Gajović).- Chabauty-Coleman computations on rank 1 Picard curves (S. Hashimoto).- Linear dependence among Hecke eigenvalues (D. Kim).- Congruent number triangles with the same hypotenuse (D. Lowry-Duda).- Visualizing modular forms (D. Lowry-Duda).- A Prym variety with everywhere good reduction over Q(√ 61) ( J. Voight).- The S-integral points on the projective line minus three points via étale covers and Skolem's method (B. Poonen).
£189.99
