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.
Author(s): Steven Kay
Publisher: Springer
Year: 2005
Language: English
Pages: 834
Title Page......Page 1
Preface......Page 5
CONTENTS......Page 8
1. Introduction......Page 16
2. Computer Simulation......Page 28
3. Basic Prob ability......Page 51
4. Conditional Probability......Page 87
5. Discrete Random Variables......Page 119
6. Expected Values for Discrete Random Variables......Page 146
7. Multiple Discrete Random Variables......Page 180
8. Condition al Probability Mass Functions......Page 227
9. Discrete N-Dimensional Random Variables......Page 259
10. Continuous Random Variables......Page 296
11. Expected Values for Continuous Random Variables......Page 354
12. Multiple Continuous RandomVariables......Page 387
13. Conditional Probability Density Functions......Page 442
14. Continuous N- Dimensional Random Variables......Page 465
15. Prob ability and MomentApproximations Using Limit Theorems......Page 492
16. Basic Random Processes......Page 522
17. Wide Sense Station ary RandomProcesses......Page 554
18. Linear Systems and Wide Sense Stationary Random Processes......Page 604
19. Multiple Wide Sense Stationary Random Processes......Page 647
20. Gaussian Random Processes......Page 678
21. Poisson Random Processes......Page 715
22. Markov Chains......Page 743
A: Glossary of Symbols and Abbrevations......Page 779
B: Assorted Math Facts and Formulas......Page 785
C: Linear and Matrix Algebra......Page 790
D: Summary of Signals , Linear Transforms, and Linear Systems......Page 796
E: Answers to Selected Problems......Page 810
INDEX......Page 824
