Applied mathematics Books

Book SynopsisPricing by Arbitrage.- Martingale Measures.- The First Fundamental Theorem.- Complete Markets.- Discrete-time American Options.- Continuous-Time Stochastic Calculus.- Continuous-Time European Options.- The American Put Option.- Bonds and Term Structure.- Consumption-Investment Strategies.- Measures of Risk.Trade ReviewFrom the reviews: "...This book is a valuable addition to a graduate student's reference collection. The number of textbooks in mathematical finance is increasing much faster than the number of revolutionary contributions to the field, but this text stands above the crowd." SIAM Review, December 2005 From the reviews of the second edition: "The book is very carefully formatted. … this book is a valuable addition to a graduate student’s reference collection. The number of textbooks in mathematical finance is increasing much faster than the number of revolutionary contributions to the field, but this text stands above the crowd." (Alexandre D’Aspremont, SIAM Reviews, December, 2005) "The emphasis of the first edition of this book was on developing the mathematical concepts for the rapidly expanding field of mathematical finance. This second edition contains a significant number of changes and additions … . The target audience is readers with sound mathematical background on elementary concepts from measure-theoretic probability … . It should be an equally valuable resource to practitioners interested in the mathematical tools … . will be a very useful addition to any scholarly library." (Theofanis Sapatinas, Journal of Applied Sciences, Vol. 32 (6), 2005) "The second edition adds new matieral from current active research areas. A new chapter on coherent risk measures for instance reflects the recent trend in research and applications in the area of risk management. In summary, this is an excellent textbook in mathematical finance, and I can definitely recommend it." (S. Peng, Short Book Reviews of the ISI, June 2006)Table of ContentsPricing by Arbitrage * Martingale Measures * The Fundamental Theorem of Asset Pricing * Complete Markets and Martingale Representation * Stopping Times and American Options * A Review of Continuous Time Stochastic Calculus * European Options in Continuous Time * The American Option * Bonds and Term Structure * Consumption-Investment Strategies *

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Book Synopsis1 Set.- 1.1 Sample sets.- 1.2 Operations with sets.- 1.3 Various relations.- 1.4 Indicator.- Exercises.- 2 Probability.- 2.1 Examples of probability.- 2.2 Definition and illustrations.- 2.3 Deductions from the axioms.- 2.4 Independent events.- 2.5 Arithmetical density.- Exercises.- 3 Counting.- 3.1 Fundamental rule.- 3.2 Diverse ways of sampling.- 3.3 Allocation models; binomial coefficients.- 3.4 How to solve it.- Exercises.- 4 Random Variables.- 4.1 What is a random variable?.- 4.2 How do random variables come about?.- 4.3 Distribution and expectation.- 4.4 Integer-valued random variables.- 4.5 Random variables with densities.- 4.6 General case.- Exercises.- Appendix 1: Borel Fields and General Random Variables.- 5 Conditioning and Independence.- 5.1 Examples of conditioning.- 5.2 Basic formulas.- 5.3 Sequential sampling.- 5.4 Pólya's urn scheme.- 5.5 Independence and relevance.- 5.6 Genetical models.- Exercises.- 6 Mean, Variance, and Transforms.- 6.1 Basic properties of expectationTrade Review"In spite of the original edition of the book being nearly thirty years old, the text still has its role to play in first and second year undergraduate probability courses. It provides an excellent foundation to more advanced courses in the subject."Short Book Reviews, Vol. 23/3, Dec. 2003 "This edition is the third revision of a text on mathematical probability first published in 1974. The text is aimed at undergraduate mathematics students and is accessible to a general audience. The prose is accurate, entertaining, and dense with historical tidbits. Two concluding chapters on mathematical finance have been added to the eight chapters in the third edition by the second author." The American Statistician, May 2004 From the reviews of the fourth edition: "The main novelty in the fourth edition of this well-written book is the addition of new chapters … . The new chapters share the friendly yet rigorous style of the former ones. They begin with an account of the financial vocabulary, which is then expounded in probabilistic terms. … Almost thirty years after its first edition, this charming book continues to be an excellent text for teaching and for self study." (Ricardo Maronna, Statistical Papers, Vol. 45 (4), 2004)Table of ContentsSet * Probability * Counting * Random Variables * Conditioning and Independence * Mean, Variance and Transforms * Poisson and Normal Distributions * From Random Walks to Markov Chains * Mean-Variance Pricing Model * Option Pricing Theory

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Book SynopsisAuthored by two of the field's most prominent researchers, this new edition has been comprehensively updated, with new material on contemporary models and methods including stochastic DEA models, material on Sharpe-ratio, and asset liability management.Table of ContentsChapter 1. Basics.- Chapter 2. Single-stage SLP models.- Chapter 3. SLP models with recourse.- Chapter 4. Algorithms.

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Book SynopsisA Course in Topological Combinatorics is the first undergraduate textbook on the field of topological combinatorics, a subject that has become an active and innovative research area in mathematics over the last thirty years with growing applications in math, computer science, and other applied areas.Trade Review“This book is an excellent introduction into the subject. … The book contains a lot of figures and each chapter ends with a group of exercises which help the reader in understanding the hard constructions and proofs. The book may serve for a one- or two-semester undergraduate course depending on the preliminary knowledges of the students.” (János Kincses, Acta Scientiarum Mathematicarum, Vol. 81 (3-4), 2015)“The present book … presents a sequence of combinatorial themes which have shown an affinity for topological methods … . This book is filled with extremely attractive mathematics … and bringing topology into the play of combinatorics and graph theory is a wonderfully elegant manoeuvre. Here it is carried out coherently, and on a pretty grand scale, and we are thus afforded the opportunity to encounter (algebraic) topology in a very seductive uniform context. What a marvelous thing!” (Michael Berg, MAA Reviews, July, 2013)“In the book’s four main chapters, Longueville (Univ. of Applied Sciences, Germany) addresses fair-division problems; graph coloring; graph property evasiveness; and embeddings and mappings. … Basic results of algebraic topology already have powerful consequences for analysis, but the subject’s arcana can look like art for art’s sake. The author’s charting of a novel application domain for a core subject makes this book an essential acquisition. Summing Up: Essential. Upper-division undergraduates and above.” (D. V. Feldman, Choice, Vol. 50 (8), April, 2013)“Topological combinatorics is concerned with the applications of the many powerful techniques of algebraic topology to problems in combinatorics. … The present book aims to give a clear and vivid presentation of some of the most beautiful and accessible results from the area. The text, based upon some courses by the author at Freie Universität Berlin, is designed for an advanced undergraduate student.” (Hirokazu Nishimura, zbMATH, Vol. 1273, 2013)Table of ContentsPreface.- List of Symbols and Typical Notation.- 1 Fair-Division Problems.- 2 Graph-Coloring Problems.- 3 Evasiveness of Graph Properties.- 4 Embedding and Mapping Problems.- A Basic Concepts from Graph Theory.- B Crash Course in Topology.- C Partially Ordered Sets, Order Complexes, and Their Topology.- D Groups and Group Actions.- E Some Results and Applications from Smith Theory.- References.- Index.

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Book Synopsis1. Universal algebra.- 2. Homological algebra.- 3. Further group theory.- 4. Algebras.- 5. Central simple algebras.- 6. Representation theory of finite groups.- 7. Noetherian rings and polynomial identities.- 8. Rings without finiteness assumptions.- 9. Skew fields.- 10. Coding theory.- 11. Languages and automata.- List of Notations.- Author Index.Trade ReviewFrom the reviews of the second volume of the revised edition: "The reader is treated to the spectacle of a very fine mathematician developing many diverse branches of algebra in a direct and illuminating manner. … this volume contains a gold-mine of algebraic nuggets, each developed in a direct and economical manner highlighting the most important results. It is an invaluable source and is to be strongly recommended." (Robert Curtis, The Mathematical Gazette, Vol. 88 (512), 2004) "The author has spent much effort at including a plentiful supply of worked concrete examples and carefully selected exercises. … it is especially the wealth of specific, non-standard topics and important applications that makes this algebra text … highly unique and valuable. … the author manages to cover a vast spectrum of concepts, methods, principles, aspects, and applications of modern algebra in a masterly style. … This introductory algebra text remains one of the very best available, all the more … in this new edition." (Werner Kleinert, Zentralblatt MATH, 1006, 2003)Table of Contents1. Universal algebra.- 2. Homological algebra.- 3. Further group theory.- 4. Algebras.- 5. Central simple algebras.- 6. Representation theory of finite groups.- 7. Noetherian rings and polynomial identities.- 8. Rings without finiteness assumptions.- 9. Skew fields.- 10. Coding theory.- 11. Languages and automata.- List of Notations.- Author Index.

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Book SynopsisContinuous Path Processes.- Continuous-Path Random Processes: Mathematical Prerequisites.- Basic Concepts and Examples in Finance.- Hitting Times: A Mix of Mathematics andFinance.- Complements on Brownian Motion.- Complements on Continuous Path Processes.- A Special Family of Diffusions: BesselProcesses.- Jump Processes.- Default Risk: An Enlargement of Filtration Approach.- Poisson Processes and Ruin Theory.- General Processes: Mathematical Facts.- Mixed Processes.- Lévy Processes.Trade Reviewconcepts of continuous-time finance … . This text presents an up-to-date account of the powerful interplay between the two areas, which is accessible yet mathematically rigorous. … This book is an accessible overview of the relevant sophisticated topics in the theory of processes, serves as an excellent guide through the literature and will doubtless become established as a standard work of reference for practitioners and researchers in the area of mathematical finance.” (Aleksandar Mijatović, Mathematical Reviews, Issue 2011 h)“Mathematical Methods for Financial Markets succeeds to be both an excellent finance textbook and an excellent maths textbook. … the work examined here is an excellent reading, going well beyond the Hull, that should be advised to all serious students in quantitative finance, and perhaps to a few colleagues who would want to enlarge their filtration about this topic. This is a prodigious encyclopaedia designed by the best authors in the field.” (Olivier Le Courtois, Revue de l'Association Française de Finance, Vol. 31 (1), 2010)Table of ContentsContinuous Path Processes.- Continuous-Path Random Processes: Mathematical Prerequisites.- Basic Concepts and Examples in Finance.- Hitting Times: A Mix of Mathematics and Finance.- Complements on Brownian Motion.- Complements on Continuous Path Processes.- A Special Family of Diffusions: Bessel Processes.- Jump Processes.- Default Risk: An Enlargement of Filtration Approach.- Poisson Processes and Ruin Theory.- General Processes: Mathematical Facts.- Mixed Processes.- Lévy Processes.

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Book Synopsis1. Introduction.- 1.1 Statistics and Their Sampling Distributions.- 1.2 The Traditional Approach.- 1.3 The Jackknife.- 1.4 The Bootstrap.- 1.5 Extensions to Complex Problems.- 1.6 Scope of Our Studies.- 2. Theory for the Jackknife.- 2.1 Variance Estimation for Functions of Means.- 2.2 Variance Estimation for Functionals.- 2.3 The Delete-d Jackknife.- 2.4 Other Applications.- 2.5 Conclusions and Discussions.- 3. Theory for the Bootstrap.- 3.1 Techniques in Proving Consistency.- 3.2 Consistency: Some Major Results.- 3.3 Accuracy and Asymptotic Comparisons.- 3.4 Fixed Sample Performance.- 3.5 Smoothed Bootstrap.- 3.6 Nonregular Cases.- 3.7 Conclusions and Discussions.- 4. Bootstrap Confidence Sets and Hypothesis Tests.- 4.1 Bootstrap Confidence Sets.- 4.2 Asymptotic Theory.- 4.3 The Iterative Bootstrap and Other Methods.- 4.4 Empirical Comparisons.- 4.5 Bootstrap Hypothesis Tests.- 4.6 Conclusions and Discussions.- 5. Computational Methods.- 5.1 The Delete-1 Jackknife.- 5.2 The Delete-d Jackknife.- 5.3 Analytic Approaches for the Bootstrap.- 5.4 Simulation Approaches for the Bootstrap.- 5.5 Conclusions and Discussions.- 6. Applications to Sample Surveys.- 6.1 Sampling Designs and Estimates.- 6.2 Resampling Methods.- 6.3 Comparisons by Simulation.- 6.4 Asymptotic Results.- 6.5 Resampling Under Imputation.- 6.6 Conclusions and Discussions.- 7. Applications to Linear Models.- 7.1 Linear Models and Regression Estimates.- 7.2 Variance and Bias Estimation.- 7.3 Inference and Prediction Using the Bootstrap.- 7.4 Model Selection.- 7.5 Asymptotic Theory.- 7.6 Conclusions and Discussions.- 8. Applications to Nonlinear, Nonparametric, and Multivariate Models.- 8.1 Nonlinear Regression.- 8.2 Generalized Linear Models.- 8.3 Cox's Regression Models.- 8.4 Kernel Density Estimation.-8.5 Nonparametric Regression.- 8.6 Multivariate Analysis.- 8.7 Conclusions and Discussions.- 9. Applications to Time Series and Other Dependent Data.- 9.1 m-Dependent Data.- 9.2 Markov Chains.- 9.3 Autoregressive Time Series.- 9.4 Other Time Series.- 9.5 Stationary Processes.- 9.6 Conclusions and Discussions.- 10. Bayesian Bootstrap and Random Weighting.- 10.1 Bayesian Bootstrap.- 10.2 Random Weighting.- 10.3 Random Weighting for Functional and Linear Models.- 10.4 Empirical Results for Random Weighting.- 10.5 Conclusions and Discussions.- Appendix A. Asymptotic Results.- A.1 Modes of Convergence.- A.2 Convergence of Transformations.- A.4 The Borel-Cantelli Lemma.- A.5 The Law of Large Numbers.- A.6 The Law of the Iterated Logarithm.- A.7 Uniform Integrability.- A.8 The Central Limit Theorem.- A.9 The Berry-Esséen Theorem.- A.10 Edgeworth Expansions.- A.11 Cornish-Fisher Expansions.- Appendix B. Notation.- References.- Author Index.Table of Contents1. Introduction.- 1.1 Statistics and Their Sampling Distributions.- 1.2 The Traditional Approach.- 1.3 The Jackknife.- 1.4 The Bootstrap.- 1.5 Extensions to Complex Problems.- 1.6 Scope of Our Studies.- 2. Theory for the Jackknife.- 2.1 Variance Estimation for Functions of Means.- 2.1.1 Consistency.- 2.1.2 Other properties.- 2.1.3 Discussions and examples.- 2.2 Variance Estimation for Functionals.- 2.2.1 Differentiability and consistency.- 2.2.2 Examples.- 2.2.3 Convergence rate.- 2.2.4 Other differential approaches.- 2.3 The Delete-d Jackknife.- 2.3.1 Variance estimation.- 2.3.2 Jackknife histograms.- 2.4 Other Applications.- 2.4.1 Bias estimation.- 2.4.2 Bias reduction.- 2.4.3 Miscellaneous results.- 2.5 Conclusions and Discussions.- 3. Theory for the Bootstrap.- 3.1 Techniques in Proving Consistency.- 3.1.1 Bootstrap distribution estimators.- 3.1.2 Mallows’ distance.- 3.1.3 Berry-Esséen’s inequality.- 3.1.4 Imitation.- 3.1.5 Linearization.- 3.1.6 Convergence in moments.- 3.2 Consistency: Some Major Results.- 3.2.1 Distribution estimators.- 3.2.2 Variance estimators.- 3.3 Accuracy and Asymptotic Comparisons.- 3.3.1 Convergence rate.- 3.3.2 Asymptotic minimaxity.- 3.3.3 Asymptotic mean squared error.- 3.3.4 Asymptotic relative error.- 3.3.5 Conclusions.- 3.4 Fixed Sample Performance.- 3.4.1 Moment estimators.- 3.4.2 Distribution estimators.- 3.4.3 Conclusions.- 3.5 Smoothed Bootstrap.- 3.5.1 Empirical evidences and examples.- 3.5.2 Sample quantiles.- 3.5.3 Remarks.- 3.6 Nonregular Cases.- 3.7 Conclusions and Discussions.- 4. Bootstrap Confidence Sets and Hypothesis Tests.- 4.1 Bootstrap Confidence Sets.- 4.1.1 The bootstrap-t.- 4.1.2 The bootstrap percentile.- 4.1.3 The bootstrap bias-corrected percentile.- 4.1.4 The bootstrap accelerated bias-corrected percentile.- 4.1.5 The hybrid bootstrap.- 4.2 Asymptotic Theory.- 4.2.1 Consistency.- 4.2.2 Accuracy.- 4.2.3 Other asymptotic comparisons.- 4.3 The Iterative Bootstrap and Other Methods.- 4.3.1 The iterative bootstrap.- 4.3.2 Bootstrap calibrating.- 4.3.3 The automatic percentile and variance stabilizing.- 4.3.4 Fixed width bootstrap confidence intervals.- 4.3.5 Likelihood based bootstrap confidence sets.- 4.4 Empirical Comparisons.- 4.4.1 The bootstrap-t, percentile, BC, and BCa.- 4.4.2 The bootstrap and other asymptotic methods.- 4.4.3 The iterative bootstrap and bootstrap calibration.- 4.4.4 Summary.- 4.5 Bootstrap Hypothesis Tests.- 4.5.1 General description.- 4.5.2 Two-sided hypotheses with nuisance parameters.- 4.5.3 Bootstrap distance tests.- 4.5.4 Other results and discussions.- 4.6 Conclusions and Discussions.- 5. Computational Methods.- 5.1 The Delete-1 Jackknife.- 5.1.1 The one-step jackknife.- 5.1.2 Grouping and random subsampling.- 5.2 The Delete-d Jackknife.- 5.2.1 Balanced subsampling.- 5.2.2 Random subsampling.- 5.3 Analytic Approaches for the Bootstrap.- 5.3.1 The delta method.- 5.3.2 Jackknife approximations.- 5.3.3 Saddle point approximations.- 5.3.4 Remarks.- 5.4 Simulation Approaches for the Bootstrap.- 5.4.1 The simple Monte Carlo method.- 5.4.2 Balanced bootstrap resampling.- 5.4.3 Centering after Monte Carlo.- 5.4.4 The linear bootstrap.- 5.4.5 Antithetic bootstrap resampling.- 5.4.6 Importance bootstrap resampling.- 5.4.7 The one-step bootstrap.- 5.5 Conclusions and Discussions.- 6. Applications to Sample Surveys.- 6.1 Sampling Designs and Estimates.- 6.2 Resampling Methods.- 6.2.1 The jackknife.- 6.2.2 The balanced repeated replication.- 6.2.3 Approximated BRR methods.- 6.2.4 The bootstrap.- 6.3 Comparisons by Simulation.- 6.4 Asymptotic Results.- 6.4.1 Assumptions.- 6.4.2 The jackknife and BRR for functions of averages.- 6.4.3 The RGBRR and RSBRR for functions of averages.- 6.4.4 The bootstrap for functions of averages.- 6.4.5 The BRR and bootstrap for sample quantiles.- 6.5 Resampling Under Imputation.- 6.5.1 Hot deck imputation.- 6.5.2 An adjusted jackknife.- 6.5.3 Multiple bootstrap hot deck imputation.- 6.5.4 Bootstrapping under imputation.- 6.6 Conclusions and Discussions.- 7. Applications to Linear Models.- 7.1 Linear Models and Regression Estimates.- 7.2 Variance and Bias Estimation.- 7.2.1 Weighted and unweighted jackknives.- 7.2.2 Three types of bootstraps.- 7.2.3 Robustness and efficiency.- 7.3 Inference and Prediction Using the Bootstrap.- 7.3.1 Confidence sets.- 7.3.2 Simultaneous confidence intervals.- 7.3.3 Hypothesis tests.- 7.3.4 Prediction.- 7.4 Model Selection.- 7.4.1 Cross-validation.- 7.4.2 The bootstrap.- 7.5 Asymptotic Theory.- 7.5.1 Variance estimators.- 7.5.2 Bias estimators.- 7.5.3 Bootstrap distribution estimators.- 7.5.4 Inference and prediction.- 7.5.5 Model selection.- 7.6 Conclusions and Discussions.- 8. Applications to Nonlinear, Nonparametric, and Multivariate Models.- 8.1 Nonlinear Regression.- 8.1.1 Jackknife variance estimators.- 8.1.2 Bootstrap distributions and confidence sets.- 8.1.3 Cross-validation for model selection.- 8.2 Generalized Linear Models.- 8.2.1 Jackknife variance estimators.- 8.2.2 Bootstrap procedures.- 8.2.3 Model selection by bootstrapping.- 8.3 Cox’s Regression Models.- 8.3.1 Jackknife variance estimators.- 8.3.2 Bootstrap procedures.- 8.4 Kernel Density Estimation.- 8.4.1 Bandwidth selection by cross-validation.- 8.4.2 Bandwidth selection by bootstrapping.- 8.4.3 Bootstrap confidence sets.- 8.5 Nonparametric Regression.- 8.5.1 Kernel estimates for fixed design.- 8.5.2 Kernel estimates for random regressor.- 8.5.3 Nearest neighbor estimates.- 8.5.4 Smoothing splines.- 8.6 Multivariate Analysis.- 8.6.1 Analysis of covariance matrix.- 8.6.2 Multivariate linear models.- 8.6.3 Discriminant analysis.- 8.6.4 Factor analysis and clustering.- 8.7 Conclusions and Discussions.- 9. Applications to Time Series and Other Dependent Data.- 9.1 m-Dependent Data.- 9.2 Markov Chains.- 9.3 Autoregressive Time Series.- 9.3.1 Bootstrapping residuals.- 9.3.2 Model selection.- 9.4 Other Time Series.- 9.4.1 ARMA(p,q) models.- 9.4.2 Linear regression with time series errors.- 9.4.3 Dynamical linear regression.- 9.5 Stationary Processes.- 9.5.1 Moving block and circular block.- 9.5.2 Consistency of the bootstrap.- 9.5.3 Accuracy of the bootstrap.- 9.5.4 Remarks.- 9.6 Conclusions and Discussions.- 10. Bayesian Bootstrap and Random Weighting.- 10.1 Bayesian Bootstrap.- 10.1.1 Bayesian bootstrap with a noninformative prior.- 10.1.2 Bayesian bootstrap using prior information.- 10.1.3 The weighted likelihood bootstrap.- 10.1.4 Some remarks.- 10.2 Random Weighting.- 10.2.1 Motivation.- 10.2.2 Consistency.- 10.2.3 Asymptotic accuracy.- 10.3 Random Weighting for Functional and Linear Models.- 10.3.1 Statistical functionals.- 10.3.2 Linear models.- 10.4 Empirical Results for Random Weighting.- 10.5 Conclusions and Discussions.- Appendix A. Asymptotic Results.- A.1 Modes of Convergence.- A.2 Convergence of Transformations.- A.4 The Borel-Cantelli Lemma.- A.5 The Law of Large Numbers.- A.6 The Law of the Iterated Logarithm.- A.7 Uniform Integrability.- A.8 The Central Limit Theorem.- A.9 The Berry-Esséen Theorem.- A.10 Edgeworth Expansions.- A.11 Cornish-Fisher Expansions.- Appendix B. Notation.- References.- Author Index.

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Book Synopsis1. Introduction.- 1.1. Order Symbols, Uniformity.- 1.2. Asymptotic Expansion of a Given Function.- 1.3. Regular Expansions for Ordinary and Partial Differential Equations.- References.- 2. Limit Process Expansions for Ordinary Differential Equations.- 2.1. The Linear Oscillator.- 2.2. Linear Singular Perturbation Problems with Variable Coefficients.- 2.3. Model Nonlinear Example for Singular Perturbations.- 2.4. Singular Boundary Problems.- 2.5. Higher-Order Example: Beam String.- References.- 3. Limit Process Expansions for Partial Differential Equations.- 3.1. Limit Process Expansions for Second-Order Partial Differential Equations.- 3.2. Boundary-Layer Theory in Viscous, Incompressible Flow.- 3.3. Singular Boundary Problems.- References.- 4. The Method of Multiple Scales for Ordinary Differential Equations.- 4.1. Method of Strained Coordinates for Periodic Solutions.- 4.2. Two Scale Expansions for the Weakly Nonlinear Autonomous Oscillator.- 4.3. Multiple-Scale Expansions for General Weakly Nonlinear Oscillators.- 4.4. Two-Scale Expansions for Strictly Nonlinear Oscillators.- 4.5. Multiple-Scale Expansions for Systems of First-Order Equations in Standard Form.- References.- 5. Near-Identity Averaging Transformations: Transient and Sustained Resonance.- 5.1. General Systems in Standard Form: Nonresonant Solutions.- 5.2. Hamiltonian System in Standard Form; Nonresonant Solutions.- 5.3. Order Reduction and Global Adiabatic Invariants for Solutions in Resonance.- 5.4. Prescribed Frequency Variations, Transient Resonance.- 5.5. Frequencies that Depend on the Actions, Transient or Sustained Resonance.- References.- 6. Multiple-Scale Expansions for Partial Differential Equations.- 6.1. Nearly Periodic Waves.- 6.2. Weakly Nonlinear Conservation Laws.- 6.3. Multiple-Scale Homogenization.- References.Table of Contents1. Introduction.- 1.1. Order Symbols, Uniformity.- 1.2. Asymptotic Expansion of a Given Function.- 1.3. Regular Expansions for Ordinary and Partial Differential Equations.- References.- 2. Limit Process Expansions for Ordinary Differential Equations.- 2.1. The Linear Oscillator.- 2.2. Linear Singular Perturbation Problems with Variable Coefficients.- 2.3. Model Nonlinear Example for Singular Perturbations.- 2.4. Singular Boundary Problems.- 2.5. Higher-Order Example: Beam String.- References.- 3. Limit Process Expansions for Partial Differential Equations.- 3.1. Limit Process Expansions for Second-Order Partial Differential Equations.- 3.2. Boundary-Layer Theory in Viscous, Incompressible Flow.- 3.3. Singular Boundary Problems.- References.- 4. The Method of Multiple Scales for Ordinary Differential Equations.- 4.1. Method of Strained Coordinates for Periodic Solutions.- 4.2. Two Scale Expansions for the Weakly Nonlinear Autonomous Oscillator.- 4.3. Multiple-Scale Expansions for General Weakly Nonlinear Oscillators.- 4.4. Two-Scale Expansions for Strictly Nonlinear Oscillators.- 4.5. Multiple-Scale Expansions for Systems of First-Order Equations in Standard Form.- References.- 5. Near-Identity Averaging Transformations: Transient and Sustained Resonance.- 5.1. General Systems in Standard Form: Nonresonant Solutions.- 5.2. Hamiltonian System in Standard Form; Nonresonant Solutions.- 5.3. Order Reduction and Global Adiabatic Invariants for Solutions in Resonance.- 5.4. Prescribed Frequency Variations, Transient Resonance.- 5.5. Frequencies that Depend on the Actions, Transient or Sustained Resonance.- References.- 6. Multiple-Scale Expansions for Partial Differential Equations.- 6.1. Nearly Periodic Waves.- 6.2. Weakly Nonlinear Conservation Laws.- 6.3. Multiple-Scale Homogenization.- References.

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Book SynopsisThis book has been written in a frankly partisian spirit-we believe that singularity theory offers an extremely useful approach to bifurcation prob­ lems and we hope to convert the reader to this view.

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Book SynopsisAlthough there are many books on mathematical finance, few deal with the statistical aspects of modern data analysis as applied to financial problems.Table of ContentsUnivariate Data Distributions.- Heavy Tail Distributions.- Dependence and Multivariate Data Exploration.- Parametric Regression.- Local and Nonparametric Regression.- Time Series Models.- Multivariate Time Series, Linear Systems and Kalman Filtering.- Nonlinear Time Series: Models and Simulation.- Appendices.- Indices.

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Book SynopsisThis book covers the basic results and methods in probability theory. This new edition offers updated content, 100 additional problems for solution, and a new chapter glimpsing further topics such as stable distributions, domains of attraction and martingales.Trade ReviewFrom the reviews of the second edition:"This is an excellent introductory book on random variables, with a wealth of examples and exercises. … The material is very well organized … . The text is remarkably well written, mathematically and aesthetically; layout and fonts make it a pleasant reading, and the examples are often enlightening. I think it will be a valuable support for students and instructors and it should definitely find a place in every good library." (Fabio Mainardi, The Mathematical Association of America, October, 2009)“…A worthwhile addition to the textbook pool, one that will guide the student safely through to a point of competence and ability to embark on a more advanced study…” (International Statistical Review, 2010, 78, 1, 134-159)“The book addresses a unique niche mathematically inclined students previously exposed to an introductory course in probability … . The writing style is lucid and easy to follow. … book is clearly directed toward mathematicians and the highly mathematically inclined scientist or engineer who might be induced to study the mathematics of probability or mathematical statistics. For those who find the classical mathematical pedagogy motivating or those requiring a comprehensive readable reference work on the mathematics of probability theory the book can be highly recommended.” (Thomas D. Sandry, Technometrics, Vol. 53 (1), February, 2011)“This book … is intended as an introductory graduate level textbook in probability for statistics majors. … This book provides an elaborate description and a collection of results in probability theory. … The level of this book is suitable for a graduate course. Overall all concepts are well discussed with full mathematical rigor. … has a good collection of most of the results related to probability theory, the price is very reasonable, and I will recommend this book to university mathematics and statistics libraries.” (Sounak Chakraborty, Journal of the American Statistical Association, Vol. 106 (495), September, 2011)Table of ContentsMultivariate Random Variables.- Conditioning.- Transforms.- Order Statistics.- The Multivariate Normal Distribution.- Convergence.- An Outlook on Further Topics.- The Poisson Process.

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Book SynopsisThis book is designed as an introductory course in Tropical Meteorology for the graduate or advanced level undergraduate student. It then goes on to progressively smaller spatial and time scales – from the El Niño Southern Oscillation and the Asian Monsoon, down to tropical waves, hurricanes, sea breezes, and tropical squall lines.Trade ReviewFrom the reviews:“The book may prove valuable to researchers, given the lack of other books on the subject. Summing Up: Recommended. … Graduate students and researchers/faculty.” (S. G. Decker, Choice, Vol. 51 (6), February, 2014) Table of ContentsThe Zonally Averaged Tropical Circulation.- Zonally Asymmetric Features in the Tropics.- The Intertropical Convergence Zone.- Heat Induced Circulations.- Monsoons.- Tropical Waves and Tropical Depressions.- The Madden Julian Oscillation.- Scale Interaction in the Tropics.- El Nino and Southern Oscillation.- Diabatic Potential Vorticity Over the Global Tropics.- Tropical Cloud Ensembles.- Tropical boundary layer.- Radiative Forcing.- Dry and moist static stability.- Hurricane Observations.- Genesis, Tracks and Intensification of Hurricanes.- Modeling and Forecasting of Hurricanes.- Sea Breeze and Diurnal Change Over the Tropics.- Tropical Squall Lines and Mesoscale convective systems.

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Book SynopsisDiscrete Structures introduces readers to the mathematical structures and methods that form the foundation of computer science and features multiple techniques that readers will turn to regularly throughout their careers in computer and information sciences.Over the course of five modules, students learn specific skills including binary and modular arithmetic, set notation, methods of counting, evaluating sums, and solving recurrences. They study the basics of probability, proof by induction, growth of functions, and analysis techniques. The book also discusses general problem-solving techniques that are widely applicable to real problems. Each module includes motivation applications, technique, theory, and further opportunities for application.Informed by extensive experience teaching in computer science programs, Discrete Structures has been developed specifically for first-year students in those programs. The material is also suitable for courses in computer engineering, as well as those for students who are transferring from other disciplines and just beginning their computer science or engineering education.

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Book SynopsisThis book examines non-Gaussian distributions. It addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The book is written for non-mathematicians who want to model financial market prices so the emphasis throughout is on practice. There are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series.Trade ReviewFrom the reviews: "Financial Modeling Under Non-Gaussian Distributions … is thus very welcome as it provides an accessible and easy-to-understand treatment of a broad range of topics, including core material to more advanced techniques on the subject of capturing non-Gaussian properties in the distributions of asset returns. … Financial Modeling Under Non-Gaussian Distributions is a very accessible textbook that covers a wide range of topics. … The authors define their target readers as specialized master and Ph.D. students, as well as financial industry practitioners." (Stephan Suess, Financial Markets and Portfolio Management, Vol. 22, 2008) "This book is written for non-mathematicians who want to model financial market prices. ... It targets practioners in the financial industry. It is suitable for use as core text for students in empirical finance, financial econometrics and financial derivatives. It is useful for mathematician who want to know more about their mathematical tools are applied in finance." (Klaus Ehemann, Zentralblatt MATH, Vol. 1138 (16), 2008)Table of ContentsFinancial Markets and Financial Time Series.- Statistical Properties of Financial Market Data.- Functioning of Financial Markets and Theoretical Models for Returns.- Econometric Modeling of Asset Returns.- Modeling Volatility.- Modeling Higher Moments.- Modeling Correlation.- Extreme Value Theory.- Applications of Non-Gaussian Econometrics.- Risk Management and VaR.- Portfolio Allocation.- Option Pricing with Non-Gaussian Returns.- Fundamentals of Option Pricing.- Non-structural Option Pricing.- Structural Option Pricing.- Appendices on Option Pricing Mathematics.- Brownian Motion and Stochastic Calculus.- Martingale and Changing Measure.- Characteristic Functions and Fourier Transforms.- Jump Processes.- Lévy Processes.

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Book SynopsisBased on a course taught for years at Oxford, this book offers a concise exposition of the central ideas of general relativity. The focus is on the chain of reasoning that leads to the relativistic theory from the analysis of distance and time measurements in the presence of gravity, rather than on the underlying mathematical structure. Includes links to recent developments, including theoretical work and observational evidence, to encourage further study.Trade ReviewFrom the reviews:“This book introduces General Relativity at students level, especially intended for final year mathematics students. Different from other books with the same title, it really goes into the geometric details and tries to explain the given formulae … . The appendices present exercises and hints to their solutions.” (Philosophy, Religion and Science Book Reviews, bookinspections.wordpress.com, May, 2014)"I have the opportunity to comment on General Relativity … . I am happy to recommend … for an advanced undergraduate course on relativity or for self-study. … marvelous faithfulness to historical developments … characterizes the entire treatment. … In fact, the whole book is distinguished by this high quality of exposition. … It’s a fine book, beautifully written and clear, and I highly recommend it." (Michael Berg, MathDL, January, 2007)MAA Reviews:In December, 2003 I had the pleasure of reviewing the admirable book Special Relativity, by N.M.J. Woodhouse, and now I have the opportunity to comment on General Relativity by the same author. I am happy to recommend not just this sequel, but the indicated pair, for an advanced undergraduate course on relativity or for self-study.One particularly noteworthy feature of General Relativity is that woodhouse seeks to present the subject neither as a branch of differential geometry nor as the kind of physics mathematicians like me find unapproachable (and I'm afraid this doesn't particularly narrow the field). When just a rookie I dabbled in relativity largely from popularizations and biographical writings, and when I tried to learn some real general relativity in graduate school - for cultural reasons, I guess - it simply didn't take. But my interest in the subject, both specially and generally, has never flagged and Woodhouse’s books are tailor-made for even my lingering ambitions. In other words, for any slacker who feels he should have learned this beautiful material in his mathematical youth, but didn’t, and is now secretly (or not so secretly) desirous of doing it right, this is the book, or, more correctly, these are the books to read. Furthermore, as I already hinted, as far as teaching courses on these important subjects is concerned, obviously these books fit that bill very well too, given Woodhouse’s specific pedagogical intent.When it comes to the specific style and presentation of general relativity chosen by Woodhouse, marvellous faithfulness to historical developments, in particular Einstein’s own writings, characterizes the entire treatment. On p.7, already, the weak and strong equivalence principles are presented and analysed in a succinct and historically rooted fashion. The former, going back to Galileo’s pendulums (Woodhouse correctly says "pendula," of course) and famously connected with Eötvös’ experiment, entails that inertial mass and gravitational mass are the same; and the latter says that there are no obvservable differences between the local effects of gravity and acceleration. Woodhouse’s brief discussion of these observable differences between the local effects of gravity and acceleration. Woodhouse’s brief discussion of these incomparable axioms underlying Einstein’s revolution is a gem of exposition, covering the historical sweep of the attendant experiments (he even mentions a planned space experiment, "STEP," which will test the latter principle to within one part in 1018) and conveying what is to come as a result of these stipulations. Finally, I want to draw special attention to pp.23-27, where Woodhouse does a phenomenally good job of explicating the subject of tensors in Minkowski space, a subject which has always been a bit unsettling to me who was raised to visit tensor products in their homological algebraic home and I cannot resist mentioning Problem 1.5 on p.13, dealing with "Einstein’s birthday present."It’s a fine book, beautifully written and clear, and I highly recommend it. [Reviewed by Michael Berg, 20.1.2007]"Woodhouse … lets the physical intuition behind relativity inform every step of its logical development, making his treatment as digestible as any in print. He does introduce ab ovo what differential geometry he needs, and he takes the whole theory far enough to develop general relativity’s most exciting predictions, black holes and gravity waves, all in less than half the number of pages one might expect. Summing Up: Highly recommended. Upper-division undergraduates through professionals." (D. V. Feldman, CHOICE, Vol. 44 (11), July, 2007)"The book is an outgrowth of a lecture course given over many years by the author and his colleagues to final-year applied mathematicians at the Mathematical Institute in Oxford, UK. The book is well-written and easy to follow because the author constructs the necessary apparatus layer-by-layer, from the bottom up, carefully motivating and justifying every new concept. Exercises are given at the end of every chapter … and numerous examples appear throughout the text. … its expository style is very appealing." (David A. Burton, General Relativity and Gravitation, Vol. 39, 2007)Table of ContentsNewtonian Gravity.- Inertial Coordinates and Tensors.- Energy-Momentum Tensors.- Curved Space—Time.- Tensor Calculus.- Einstein’s Equation.- Spherical Symmetry.- Orbits in the Schwarzschild Space—Time.- Black Holes.- Rotating Bodies.- Gravitational Waves.- Redshift and Horizons.

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Book SynopsisFirst published in 1987, this text offers concise but clear explanations and derivations to give readers a confident grasp of the chain of argument that leads from Newton’s laws through Lagrange’s equations and Hamilton’s principle, to Hamilton’s equations and canonical transformations. This new edition has been extensively revised and updated to include: A chapter on symplectic geometry and the geometric interpretation of some of the coordinate calculations. A more systematic treatment of the conections with the phase-plane analysis of ODEs; and an improved treatment of Euler angles. A greater emphasis on the links to special relativity and quantum theory showing how ideas from this classical subject link into contemporary areas of mathematics and theoretical physics. A wealth of examples show the subject in action and a range of exercises – with solutions – are provided to help test understanding. Trade ReviewFrom the reviews of the second edition:“It is designed to teach analytical mechanics to second and third year undergraduates in the UK, and probably to third or fourth year undergraduates in the US. … This book offers a very attractive traditional introduction to the subject. … the author is well tuned to the difficulties even strong students encounter. … discusses the relevance of classical mechanics in modern physics, especially to relativity and quantum mechanics. This is a fine textbook. It would be a pleasure to teach or to learn from it.” (William J. Satzer, The Mathematical Association of America, March, 2010)Table of ContentsFrames of Reference.- One Degree of Freedom.- Lagrangian Mechanics.- Noether#x2019;s Theorem.- Rigid Bodies.- Oscillations.- Hamiltonian Mechanics.- Geometry of Classical Mechanics.- Epilogue: Relativity and Quantum Theory.

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Book SynopsisThis book provides readers with the tools needed to understand the physical basis of special relativity and will enable a confident mathematical understanding of Minkowski's picture of space-time. It features a large number of examples and exercises, ranging from the rather simple through to the more involved and challenging. Coverage includes acceleration and tensors and has an emphasis on space-time diagrams.Trade ReviewFrom the reviews: N.M.J. Woodhouse's comparatively short Special Relativity is a pleasure to read and therefore qualifies right off as a good source to use for learning about special relativity on your own. A lot of very nice material is touched on in its pages, presented in natural sequence consonant with history, and is not improperly belabored. It's also rather informal in style. One gets the sense of breezing along pretty fast while, in actuality, a lot of material is being dealt with... the selection of topics in the book is very nice indeed , and is historically sound and will therefore reward the reader with an element of culture to boot: he'll learn some history of modern physics... I wish this book had been around when I was a student. MAA Online ...an exciting and challenging book with which to introduce a modern mathematics student in a single course to the great ideas of Maxwell's theory and special relativity. The Australian Mathematical Society Gazette "There are many books on special relativity for undergraduates, and this one is notable in that it is specifically addressed to mathematicians. … this book will be found illuminating by students of mathematics … ." (Dr. P. E. Hodgson, Contemporary Physics, Vol. 45 (5), 2004) "This book is … aimed squarely at the undergraduate mathematician ... . The tone, pace and level of the book are nicely judged for middle level undergraduates studying mathematics. … There are lots of examples and nicely graded exercises throughout the text, and each chapter ends with a usefully annotated bibliography. The author’s friendly style, and the fact the material has been developed from taught courses make the book ideal for self-study … ." (Peter Macgregor, The Mathematical Gazette, Vol. 88 (512), 2004) "Meant as a resource for advanced undergraduate students, this book approaches special relativity theory from a mathematical perspective … . It is best used for mathematics majors … . the text is clear, well written, and has an adequate bibliography. Summing Up: Recommended. Upper-division undergraduates." (A. Spero, CHOICE, December, 2003) "This presentation is very elegant … . The book contains a large number of examples. Each chapter is followed by exercises, ranging from the rather simple to the more involved. This book is certainly a good introduction to special relativity, understandable for second-year students. But it is also interesting for readers searching for a concise and precise presentation of special relativity within the tensor formalism." (Claude Semay, Physcalia, Vol. 25 (4), 2003)Table of Contents1. Relativity in Classical Mechanics.- 1.1 Frames of Reference.- 1.2 Relativity.- 1.3 Frames of Reference.- 1.4 Newton’s Laws.- 1.5 Galilean Transformations.- 1.6 Mass, Energy, and Momentum.- 1.7 Space-time.- 1.8 *Galilean Symmetries.- 1.9 Historical Note.- 2. Maxwell’s Theory.- 2.1 Introduction.- 2.2 The Unification of Electricity and Magnetism.- 2.3 Charges, Fields, and the Lorentz Force Law.- 2.4 Stationary Distributions of Charge.- 2.5 The Divergence of the Magnetic Field.- 2.6 Inconsistency with Galilean Relativity.- 2.7 The Limits of Galilean Invariance.- 2.8 Faraday’s Law of Induction.- 2.9 The Field of Charges in Uniform Motion.- 2.10 Maxwell’s Equations.- 2.11 The Continuity Equation.- 2.12 Conservation of Charge.- 2.13 Historical Note.- 3. The Propagation of Light.- 3.1 The Displacement Current.- 3.2 The Source-free Equations.- 3.3 The Wave Equation.- 3.4 Monochromatic Plane Waves.- 3.5 Polarization.- 3.6 Potentials.- 3.7 Gauge Transformations.- 3.8 Photons.- 3.9 Relativity and the Propagation of Light.- 3.10 The Michelson-Morley Experiment.- 4. Einstein’s Special Theory of Relativity.- 4.1 Lorentz’s Contraction.- 4.2 Operational Definitions of Distance and Time.- 4.3 The Relativity of Simultaneity.- 4.4 Bondi’s fc-Factor.- 4.5 Time Dilation.- 4.6 The Two-dimensional Lorentz Transformation.- 4.7 Transformation of Velocity.- 4.8 The Lorentz Contraction.- 4.9 Composition of Lorentz Transformations.- 4.10 Rapidity.- 4.11 *The Lorentz and Poincaré Groups.- 5. Lorentz Transformations in Four Dimensions.- 5.1 Coordinates in Four Dimensions.- 5.2 Four-dimensional Coordinate Transformations.- 5.3 The Lorentz Transformation in Four Dimensions.- 5.4 The Standard Lorentz Transformation.- 5.5 The General Lorentz Transformation.- 5.6 Euclidean Space and Minkowski Space.- 5.7 Four-vectors.- 5.8 Temporal and Spatial Parts.- 5.9 The Inner Product.- 5.10 Classification of Four-vectors.- 5.11 Causal Structure of Minkowski Space.- 5.12 Invariant Operators.- 5.13 The Frequency Four-vector.- 5.14 * Affine Spaces and Covectors.- 6. Relative Motion.- 6.1 Transformations Between Frames.- 6.2 Proper Time.- 6.3 Four-velocity.- 6.4 Four-acceleration.- 6.5 Constant Acceleration.- 6.6 Continuous Distributions.- 6.7 *Rigid Body Motion.- 6.8 Visual Observation.- 7. Relativistic Collisions.- 7.1 The Operational Definition of Mass.- 7.2 Conservation of Four-momentum.- 7.3 Equivalence of Mass and Energy.- 8. Relativistic Electrodynamics.- 8.1 Lorentz Transformations of E and B.- 8.2 The Four-Current and the Four-potential.- 8.3 Transformations of E and B.- 8.4 Linearly Polarized Plane Waves.- 8.5 Electromagnetic Energy.- 8.6 The Four-momentum of a Photon.- 8.7 *Advanced and Retarded Solutions.- 9. *Tensors and Isomet ries.- 9.1 Affine Space.- 9.2 The Lorentz Group.- 9.3 Tensors.- 9.4 The Tensor Product.- 9.5 Tensors in Minkowski Space.- 9.6 Tensor Components.- 9.7 Examples of Tensors.- 9.8 One-parameter Subgroups.- 9.9 Isometries.- 9.10 The Riemann Sphere and Spinors.- Notes on Exercises.- Vector Calculus.

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Book SynopsisThis book serves as an introduction to the use of mathematics in describing collective phenomena in physics and biology. Derived from a course of innovative lectures, the book shows students early in their studies how many of the topics they have encountered – partial differential equations, differential equations, Fourier series, and linear algebra – are useful in constructing, analysing and interpreting phenomena present in the real world. Throughout, ideas are developed using worked examples and exercises with solution. The text does not assume a strong background in physics. Trade ReviewFrom the reviews: "This textbook … is designed for undergraduates who have followed a first ‘mathematical methods’ course and who are ready to study in more depth the mathematics underlying phenomena … . Each chapter includes a number of worked examples and a dozen or so exercises, with solutions collected at the end of the book. The book is aimed at students of applied mathematics, physics and engineering. The emphasis on techniques and the frequent references to applications make it particularly suitable for this audience." (S.C. Russen, The Mathematical Gazette, Vol. 89 (516), 2005) "Fields, Flows, and Waves, is an introduction to continuum models based on the author’s lectures … . Ample illustrations and worked examples come with the exposition, and there are several exercises with varying degrees of difficulty; detailed solutions are included at the end of the text. … I warmly recommend this book. It reads well and is in an attractive, concise format. … It makes one yearn for a course in the curriculum where this material could be regularly taught." (SIAM Review, Vol. 46 (3), 2004) "This book is an introduction to the mathematical methods in classical fields theory. It is designed for the second-year undergraduate in physics, mathematics and engineering. … The presentation is excellent, numerous examples of increasing difficulties are considered with details. … The book ends with solutions to the exercises a short bibliography and an index. In conclusion, I warmly recommend this book to any students in physics because it’s well written … interesting and very useful." (Stéphane Métens, Physicalia, Vol. 26 (1), 2004) "This book … is a first introduction to the mathematical description of fields, flows and waves. It shows students, early in their studies, how many of the topics they have encountered are useful … . Designed for second-year undergraduate students in mathematics, mathematical physics, and engineering, it presumes only a limited familiarity with several variable calculus and vector fields. … The ideas are developed through worked examples, and a range of exercises (with solutions) is provided to test understanding." (Läenseignement Mathematique, Vol. 49 (3-4), 2003) "This is another excellent readable book in the Springer Undergraduate Mathematics Series (SUMS). It is a refreshingly modern approach to Continuum Mechanics … . Indeed Professor Parker has written this book so that it might be used directly as an elementary course … . This is a carefully written, well structured book which contains a wealth of examples complete with solutions. … a carefully structured book from which a modern undergraduate applied mathematics course may be taught directly." (Sean McKee, Journal of Fluid Mechanics, Vol.504, 2004) "Introductory books … often struggle with the balance between the motivating physical problems and the formal mathematical structures. As the title suggests, Parker … manages to keep the more technical mathematical structure in clear view. Particularly impressive is how carefully the author leads readers … . the book has a completeness that makes it attractive as a self-contained resource as well as a textbook. … complete solutions (not just answers) to all of the exercises makes the book particularly effective for independent study of this material. Summing Up: Highly recommended." (J. Feroe, CHOICE, December, 2003) "The book is well-written and illustrated by interesting figures which make the text easy to read and attractive. Of course undergraduate students in physics and maybe in mathematics will surely benefit of a lecture and practice of this book. Each of the ten chapters indeed contains some lists of significant exercises. The more or less detailed solutions of these exercises are gathered at the end of the book." (Alain Brillard, Zentralblatt MATH, 2003) "Continuum models ignoring the substructures of fluids are useful and widely applied for the description of fields, flows, and waves in different research works. This book gives a first introduction to the mathematical methods necessary for the solution of the resulting equations. … Each chapter contains some examples and exercises. … The results of the exercises are listed at the end of the book. … the book is a useful introduction in this important branch of knowledge." (Bernd Platzer, www.zamm-journal.org, 2004) "David Parker’s book Fields, Flows and Waves: An Introduction to Continuum Models … is a fine addition to the Springer Undergraduate Mathematics Series. … For the subjects considered, the author provides masterly compact accounts of the physical phenomena … and solves interesting problems. Parker takes particular care to examine the physical implications of the mathematical solutions … . An adequate selection of student exercises is included, with solutions … . could be used to enrich an advanced undergraduate or beginning graduate course on continuum mechanics." (James Casey, Physics today, October, 2004)Table of Contents1. The Continuum Description.- 1.1 Densities and Fluxes.- 1.2 Conservation and Balance Laws in One Dimension.- 1.3 Heat Flow.- 1.4 Steady Radial Flow in Two Dimensions.- 1.5 Steady Radial Flow in Three Dimensions.- 2. Unsteady Heat Flow.- 2.1 Thermal Energy.- 2.1.1 Heat Balance in One-dimensional Problems.- 2.1.2 Some Special Solutions of Equation (2.3).- 2.2 Effects of Heat Supply.- 2.3 Unsteady, Spherically Symmetric Heat Flow.- 3. Fields and Potentials.- 3.1 Gradient of a Scalar.- 3.1.1 Some Applications.- 3.2 Gravitational Potential.- 3.2.1 Special Properties of the Function ?=r?1.- 3.3 Continuous Distributions of Mass.- 3.4 Electrostatics.- 3.4.1 Gauss’s Law of Flux.- 3.4.2 Charge-free Regions.- 3.4.3 Surface Charge Density.- 4. Laplace’s Equation and Poisson’s Equation.- 4.1 The Ubiquitous Laplacian.- 4.2 Separable Solutions.- 4.3 Poisson’s Equation.- 4.4 Dipole Solutions.- 4.4.1 Uses of Dipole Solutions to ?2?=0.- 4.4.2 Spherical Inclusions.- 5. Motion of an Elastic String.- 5.1 Tension and Extension; Kinematics and Dynamics.- 5.1.1 Dynamics.- 5.2 Planar Motions.- 5.2.1 Small Transverse Motions.- 5.2.2 Longitudinal Motions.- 5.3 Properties of the Wave Equation.- 5.3.1 Standing Waves.- 5.3.2 Superposition of Standing Waves.- 5.4 D’Alembert’s Solution, Travelling Waves and Wave Reflections.- 5.4.1 Wave Reflections.- 5.5 Other One-dimensional Waves.- 5.5.1 Acoustic Vibrations in a’ lUbe.- 5.5.2 Telegraphy and High-voltage Transmission.- 6. Fluid Flow.- 6.1 Kinematics and Streamlines.- 6.1.1 Some Important Examples of Steady Flow.- 6.2 Volume Flux and Mass Flux.- 6.2.1 Incompressible Fluids.- 6.2.2 Mass Conservation.- 6.3 Two-dimensional Flows of Incompressible Fluids.- 6.3.1 The Continuity Equation.- 6.3.2 Irrotational Flows and the Velocity Potential.- 6.3.3 The Stream Function.- 6.4 Pressure in a Fluid.- 6.4.1 Resultant Force.- 6.4.2 Hydrostatics and Archimedes’ Principle.- 6.4.3 Momentum Density and Momentum Flux.- 6.5 Bernoulli’s Equation.- 6.5.1 The Material (Advected) Derivative.- 6.5.2 Bernoulli’s Equation and Dynamic Pressure.- 6.5.3 The Principle of Aerodynamic Lift.- 6.6 Three-dimensional, Incompressible Flows.- 6.6.1 The Continuity Equation.- 6.6.2 Irrotational Flows, the Velocity Potential and Laplace’s Equation.- 7. Elastic Deformations.- 7.1 The Kinematics of Deformation.- 7.1.1 Deformation Gradient.- 7.1.2 Stretch and Rotation.- 7.2 Polar Decomposition.- 7.3 Stress.- 7.3.1 Traction Vectors.- 7.3.2 Components of Stress.- 7.3.3 Traction on a General Surface.- 7.4 Isotropic Linear Elasticity.- 7.4.1 The Constitutive Law.- 7.4.2 Stretching, Shear and Torsion.- 8. Vibrations and Waves.- 8.1 Wave Reflection and Refraction.- 8.1.1 Use of the Complex Exponential.- 8.1.2 Plane Waves.- 8.1.3 Reflection at a Rigid Wall.- 8.1.4 Refraction at an Interface.- 8.1.5 Total Internal Reflection.- 8.2 Guided Waves.- 8.2.1 Acoustic Waves in a Layer.- 8.2.2 Waveguides and Dispersion.- 8.3 Love Waves in Elasticity.- 8.4 Elastic Plane Waves.- 8.4.1 Elastic Shear Waves.- 8.4.2 Dilatational Waves.- 9. Electromagnetic VVaves and Light.- 9.1 Physical Background.- 9.1.1 The Origin of Maxwell’s Equations.- 9.1.2 Plane Electromagnetic Waves.- 9.1.3 Reflection and Refraction of Electromagnetic Waves.- 9.2 Waveguides.- 9.2.1 Rectangular Waveguides.- 9.2.2 Circular Cylindrical Waveguides.- 9.2.3 An Introduction to Fibre Optics.- 10. Chemical and Biological Models.- 10.1 Diffusion of Chemical Species.- 10.1.1 Fick’s Law of Diffusion.- 10.1.2 Self-similar Solutions.- 10.1.3 Travelling Wavefronts.- 10.2 Population Biology.- 10.2.1 Growth and Dispersal.- 10.2.2 Fisher’s Equation and Self-limitation.- 10.2.3 Population-dependent Dispersivity.- 10.2.4 Competing Species.- 10.2.5 Diffusive Instability.- 10.3 Biological Waves.- 10.3.1 The Logistic Wavefront.- 10.3.2 Travelling Pulses and Spiral Waves.- Solutions.

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