Intuitive Probability and Random Processes using MATLAB®

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About this book

Intuitive Probability and Random Processes using MATLAB® is an introduction to probability and random processes that merges theory with practice. Based on the author’s belief that only "hands-on" experience with the material can promote intuitive understanding, the approach is to motivate the need for theory using MATLAB examples, followed by theory and analysis, and finally descriptions of "real-world" examples to acquaint the reader with a wide variety of applications. The latter is intended to answer the usual question "Why do we have to study this?" Other salient features are:

*heavy reliance on computer simulation for illustration and student exercises

*the incorporation of MATLAB programs and code segments

*discussion of discrete random variables followed by continuous random variables to minimize confusion

*summary sections at the beginning of each chapter

*in-line equation explanations

*warnings on common errors and pitfalls

*over 750 problems designed to help the reader assimilate and extend the concepts

Intuitive Probability and Random Processes using MATLAB® is intended for undergraduate and first-year graduate students in engineering. The practicing engineer as well as others having the appropriate mathematical background will also benefit from this book.

About the Author

Steven M. Kay is a Professor of Electrical Engineering at the University of Rhode Island and a leading expert in signal processing. He has received the Education Award "for outstanding contributions in education and in writing scholarly books and texts. " from the IEEE Signal Processing society and has been listed as among the 250 most cited researchers in the world in engineering.

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Table of contents (22 chapters)

Front Matter

Pages i-xviii

Introduction

Computer Simulation

Pages 13-36

Basic Probability

Pages 37-72

Conditional Probability

Pages 73-104

Discrete Random Variables

Pages 105-131

Expected Values for Discrete Random Variables

Pages 133-166

Multiple Discrete Random Variables

Pages 167-214

Conditional Probability Mass Functions

Pages 215-246

Discrete N-Dimensional Random Variables

Pages 247-283

Continuous Random Variables

Pages 285-342

Expected Values for Continuous Random Variables

Pages 343-376

Multiple Continuous Random Variables

Pages 377-431

Conditional Probability Density Functions

Pages 433-455

Continuous N-Dimensional Random Variables

Pages 457-483

Probability and Moment Approximations Using Limit Theorems

Pages 485-514

Basic Random Processes

Pages 515-546

Wide Sense Stationary Random Processes

Pages 547-596

Linear Systems and Wide Sense Stationary Random Processes

Pages 597-639

Multiple Wide Sense Stationary Random Processes

Pages 641-671

Reviews

From the reviews:

"The book is composed of 22 chapters. … This is a very readable book. … Kay’s book undoubtedly will see its greatest use in engineering schools, but I think it would work nicely in other settings as well. … It is written in a clear and informal style that students will appreciate, its coverage is excellent, and the author’s stated objective (to lessen the difficulty that students usually experience assimilating and applying probability and random processes) will, I predict, be met." (Ralph P. Russo, The American Statistician, Vol. 62 (2), May, 2008)

“Kay’s book occupies a unique place in the overcrowded market of textbooks on probability and random processes. … This new textbook is a breath of fresh air in the market of books devoted to probability and random processes. The book lives up to its ambition of setting a new standard for a modern, computer-based treatment of the subject. … I fully recommend its use in undergraduate and first-year graduate courses.” (Osvaldo Simeone, IEEE Control Systems Magazine, Vol. 27, June, 2007)

Authors and Affiliations

Dept. of Electrical & Computer Engineering, University of Rhode Island, Kingston, USA

Bibliographic Information