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经典英文原版概率论与随机过程教材 Roy & Yates.pdf

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    Cover
    Title Page
    Copyright
    Features of this Text
    Who will benefit from using this text?
    What's New?
    Notable Features
    Instructor Support
    Preface
    Welcome to the third edition
    How the book is organized
    What is distinctive about this book?
    Further Reading
    Acknowledgments
    A Message to Students from the Authors
    Contents
    Chapter 1: Experiments, Models, and Probabilities
    Getting Started with Probability
    1.1 Set Theory
    1.2 Applying Set Theory to Probability
    1.3 Probability Axioms
    1.4 Conditional Probability
    1.5 Partitions and the Law of Total Probability
    1.6 Independence
    1.7 Matlab
    Problems
    Chapter 2: Sequential Experiments
    2.1 Tree Diagrams
    2.2 Counting Methods
    2.3 Independent Trials
    2.4 Reliability Analysis
    2.5 Matlab
    Problems
    Chapter 3: Discrete Random Variables
    3.1 Definitions
    3.2 Probability Mass Function
    3.3 Families of Discrete Random Variables
    3.4 Cumulative Distribution Function (CDF)
    3.5 Averages and Expected Value
    3.6 Functions of a Random Variable
    3.7 Expected Value of a Derived Random Variable
    3.8 Variance and Standard Deviation
    3.9 Matlab
    Problems
    Chapter 4: Continuous Random Variables
    4.1 Continuous Sample Space
    4.2 The Cumulative Distribution Function
    4.3 Probability Density Function
    4.4 Expected Values
    4.5 Families of Continuous Random Variables
    4.6 Gaussian Random Variables
    4.7 Delta Functions, Mixed Random Variables
    4.8 Matlab
    Problems
    Chapter 5: Multiple Random Variables
    5.1 Joint Cumulative Distribution Function
    5.2 Joint Probability Mass Function
    5.3 Marginal PMF
    5.4 Joint Probability Density Function
    5.5 Marginal PDF
    5.6 Independent Random Variables
    5.7 Expected Value of a Function of Two Random Variables
    5.8 Covariance, Correlation and Independence
    5.9 Bivariate Gaussian Random Variables
    5.10 Multivariate Probability Models
    5.11 Matlab
    Problems
    Chapter 6: Probability Models of Derived Random Variables
    6.1 PMF of a Function of Two Discrete Random Variables
    6.2 Functions Yielding Continuous Random Variables
    6.3 Functions Yielding Discrete or Mixed Random Variables
    6.4 Continuous Functions of Two Continuous Random Variables
    6.5 PDF of the Sum of Two Random Variables
    6.6 Matlab
    Problems
    Chapter 7: Conditional Probability Models
    7.1 Conditioning a Random Variable by an Event
    7.2 Conditional Expected Value Given an Event
    7.3 Conditioning Two Random Variables by an Event
    7.4 Conditioning by a Random Variable
    7.5 Conditional Expected Value Given a Random Variable
    7.6 Bivariate Gaussian Random Variables: Conditional PDFs
    7.7 Matlab
    Problems
    Chapter 8: Random Vectors
    8.1 Vector Notation
    8.2 Independent Random Variables and Random Vectors
    8.3 Functions of Random Vectors
    8.4 Expected Value Vector and Correlation Matrix
    8.5 Gaussian Random Vectors
    8.6 Matlab
    Problems
    Chapter 9: Sums of Random Variables
    9.1 Expected Values of Sums
    9.2 Moment Generating Functions
    9.3 MGF of the Sum of Independent Random Variables
    9.4 Random Sums of Independent Random Variables
    9.5 Central Limit Theorem
    9.6 Matlab
    Problems
    Chapter 10: The Sample Mean
    10.1 Sample Mean: Expected Value and Variance
    10.2 Deviation of a Random Variable from the Expected Value
    10.3 Laws of Large Numbers
    10.4 Point Estimates of Model Parameters
    10.5 Confidence Intervals
    10.6 Matlab
    Problems
    Chapter 11: Hypothesis Testing
    11.1 Significance Testing
    11.2 Binary Hypothesis Testing
    11.3 Multiple Hypothesis Test
    11.4 Matlab
    Problems
    Chapter 12: Estimation of a Random Variable
    12.1 Minimum Mean Square Error Estimation
    12.2 Linear Estimation of X given Y
    12.3 MAP and ML Estimation
    12.4 Linear Estimation of Random Variables from Random Vectors
    12.5 Matlab
    Problems
    Chapter 13: Stochastic Processes
    13.1 Definitions and Examples
    13.2 Random Variables from Random Processes
    13.3 Independent, Identically Distributed Random Sequences
    13.4 The Poisson Process
    13.5 Properties of the Poisson Process
    13.6 The Brownian Motion Process
    13.7 Expected Value and Correlation
    13.8 Stationary Processes
    13.9 Wide Sense Stationary Stochastic Processes
    13.10 Cross-Correlation
    13.11 Gaussian Processes
    13.12 Matlab
    Problems
    Appendix A: Families of Random Variables
    A.1 Discrete Random Variables
    A.2 Continuous Random Variables
    Appendix B: A Few Math Facts
    Trigonometric Identities
    Sequences and Series
    Calculus
    Vectors and Matrices
    References
    Index
    Probability and Stochastic Processes
    Features of this Text Who will benefit from using this text? This text can be used in Junior or Senior level courses in probability and stochastic processes. The mathematical exposition will appeal to students and practitioners in many areas. The examples, quizzes, and problems are typical of those encountered by practicing electrical and computer engineers. Professionals in the telecommuni- cations and wireless industry will find it particularly useful. What’s New? This text has been expanded with new introductory material: tional Probability Models. • Over 160 new homework problems • New chapters on Sequential Trials, Derived Random Variables and Condi- • Matlab examples and problems give students hands-on access to theory and applications. Every chapter includes guidance on how to use Matlab to perform calculations and simulations relevant to the subject of the chapter. • Advanced material online in Signal Processing and Markov Chains supple- ments. Notable Features The Friendly Approach The friendly and accessible writing style gives students an intuitive feeling for the formal mathematics. Quizzes and Homework Problems An extensive collection of in-chapter quizzes provides checkpoints for read- ers to gauge their understanding. Hundreds of end-of-chapter problems are clearly marked as to their degree of difficulty from beginner to expert. Student Companion Website www.wiley.com/college/yates Available for download: All Matlab m-files in the text, the Quiz Solutions Manual, aStudent Solutions Manual, the Signal Processing Supplement, and the Markov Chains Supplement. Instructor Support Instructors can register for the Instructor Companion Site at www.wiley.com/ college/yates
    Probability and Stochastic Processes A Friendly Introduction for Electrical and Computer Engineers Third Edition Roy D. Yates Rutgers, The State University of New Jersey David J. Goodman New York University
    V.P. & Executive Publisher Executive Editor Sponsoring Editor Project Editor Production Editor Cover Designer Don Fowley Dan Sayre Mary O’Sullivan Ellen Keohane Eugenia Lee Samantha Low This book was set in Computer Modern by the authors using LATEX and printed and bound by RRDonnelley. The cover was printed by RRDonnelley. About the cover: The cover shows a circumhorizontal arc. As noted in Wikipedia, this is an ice-halo formed by plate-shaped ice crystals in high level cirrus clouds. The misleading term “fire rainbow” is sometimes used to describe this rare phenomenon, although it is neither a rainbow, nor related in any way to fire. This book is printed on acid-free paper. Founded in 1807, John Wiley & Sons, Inc. has been a valued source of knowledge and understanding for more than 200 years, helping people around the world meet their needs and fulfi ll their aspirations. Our company is built on a foundation of principles that include responsibility to the communities we serve and where we live and work. In 2008, we launched a Corporate Citizenship Initiative, a global eff ort to address the environmental, social, economic, and ethical challenges we face in our business. Among the issues we are addressing are carbon impact, paper specifi cations and procurement, ethical conduct within our business and among our vendors, and community and charitable support. For more information, please visit our website: www.wiley.com/go/citizenship. Copyright c 2014 John Wiley & Sons, Inc. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except as permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc. 222 Rosewood Drive, Danvers, MA 01923, website www .copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030- 5774, (201)748-6011, fax (201)748-6008, website http://www.wiley.com/go/permissions. Evaluation copies are provided to qualifi ed academics and professionals for review purposes only, for use in their courses during the next academic year. These copies are licensed and may not be sold or transferred to a third party. Upon completion of the review period, please return the evaluation copy to Wiley. Return instructions and a free of charge return mailing label are available at www.wiley.com/go/returnlabel. If you have chosen to adopt this textbook for use in your course, please accept this book as your complimentary desk copy. Outside of the United States, please contact your local sales representative. ISBN 978-1-118-32456-1 Printed in the United States of America 10 9 8 7 6 5 4 3 2 1
    To Alissa, Brett, Daniel, Hannah, Leila, Milo, Theresa, Tony, and Zach
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