【簡介】 This volume offers a comprehensive collection of exercises, problems, and fully worked solutions covering the core topics of a first course in probability. Each chapter opens with a concise overview of essential probabilistic tools — such as distributions, transforms, martingales, and Gaussian processes — followed by examples that illustrate key techniques and applications. This substantially revised second edition introduces numerous new exercises, enhances the treatment of discrete and continuous distributions, and includes strengthened sections on martingale inequalities and Gaussian processes. Ideal for building intuition and confidence, the book provides clear reasoning, rigorous solutions, and broad coverage of classical and modern topics in probability and stochastic processes. 【目錄】
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【簡介】 Probability and Stochastic Processes – A Friendly Introduction for Electrical and Computer Engineers, Fourth Edition serves as an accessible guide for engineering students delving into the realms of probability theory and stochastic processes.This text strikes a balance between rigorous mathematical exposition and clear, intuitive explanations, ensuring that students grasp the fundamental concepts essential for applying mathematics to real-world engineering challenges. Enhanced with the practical MATLAB applications. The book offers students valuable hands-on experienceto reinforce the theoretical material. This International adaptation has been thoroughly revised and updated. Notably, it includes a new chapter on Probabilistic Inequalities and Bounds. The sections on Stochastic Processes and Sums of Random Variables have been comprehensively enhanced to encompass additional topics, aligning with the latest curriculum requirements. With an array of new and updated examples, quizzes, and end-of-chapter problems, the book provides robust support to students, particularly in bridging the gap between theoretical probability and its practical applications in engineering. 【目錄】 1 Random Experiments, Models, and Probabilities 2 Sequential Random Experiments 3 Discrete Random Variables 4 Continuous Random Variables 5 Multiple Random Variables 6 Probability Models of Derived Random Variables 7 Conditional Probability Models 8 Random Vectors 9 Sums of Random Variables 10 Hypothesis Testing 11 Estimation of a Random Variable 12 Some Probabilistic Inequalities and Bounds 13 Stochastic Processes and Markov Chains 14 Stationary Processes and Random Signal Processing Appendix A The Sample Mean Appendix B Families of Random Variables Appendix C A Few Math Facts
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原文書資訊 書名:Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers 3/E IE 2014 <JW> 作者: YATES ISBN: 9781118808719 出版社: John Wiley 出版年: 2014年 中文書資訊 書名: 機率學(Yates 3/E) Probability and Stochastic Processes 作者: Yates/ 賴玲瑩 ISBN: 9789865647230 出版社: 鼎隆 出版年: 2015年
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【簡介】 【目錄】
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The book is intended to undergraduate students, it presents exercices and problems with rigorous solutions covering the mains subject of the course with both theory and applications. The questions are solved using simple mathematical methods: Laplace and Fourier transforms provide direct proofs of the main convergence results for sequences of random variables. The book studies a large range of distribution functions for random variables and processes: Bernoulli, multinomial, exponential, Gamma, Beta, Dirichlet, Poisson, Gaussian, Chi2, ordered variables, survival distributions and processes, Markov chains and processes, Brownian motion and bridge, diffusions, spatial processes. Sample Chapter(s) Preface Chapter 1: Probability measures and spaces Errata(s) Errata Request Inspection Copy Contents: Probability Measures and Spaces Probability Distributions Generating Function and Discrete Distributions Laplace Transform and Characteristic Function Continuous Distributions Empirical Processes and Weak Convergence Discrete Martingales and Stopping Times Time-Continuous Martingales Jump Processes Continuous Processes Readership: Undergraduate students interested in more advanced statistics.
