Intuitive Probability and Random Processes using MATLAB

Description

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. Cover Preface Contents 1 - Introduction 2 - Computer Simulation 3 - Basic Probability 4 - Conditional Probability 5 - Discrete Random Variables 6 - Expected Values for Discrete Random Variables 7 - Multiple Discrete Random Variables 8 - Conditional Probability Mass Functions 9 - Discrete N-Dimensional Random Variables 10 - Continuous Random Variables 11 - Expected Values for Continuous Random Variables 12 - Multiple Continuous Random Variables 13 - Conditional Probability Density Functions 14 - Continuous N-Dimensional Random Variables 15 - Probability and Moment Approximations Using LimitTheorems 16 - Basic Random Processes 17 - Wide Sense Stationary Random Processes 18 - Linear Systems and Wide Sense Stationary Random Processes 19 - Multiple Wide Sense Stationary Random Processes 20 - Gaussian Random Processes 21 - Poisson Random Processes 22 - Markov Chains Appendix A - Glossary of Symbols and Abbrevations Appendix B - Assorted Math Facts andFormulas Appendix C - Linear and Matrix Algebra Appendix D - Summary of Signals, Linear Transforms and Linear Systems Appendix E - Answers to Selected Problems Index