Textbook
Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers, 2nd EditionMay 2004, ©2005

Preface.
1. Experiments, Models, and Probabilities.
2. Discrete Random Variables.
3. Continuous Random Variables.
4. Pairs of Random Variables.
5. Random Vectors.
6. Sums of Random Variables.
7. Parameter Estimation Using the Sample Mean.
8. Hypothesis Testing.
9. Estimation of a Random Variable.
10. Stochastic Processes.
11. Random Signal Processing.
12. Markov Chains.
Appendix A: Families of Random Variables.
Appendix B: A Few Math Facts.
References.
Index.
David J. Goodman is Director of WINLAB and a Professor of Electrical and Computer Engineering at Rutgers University. Before coming to Rutgers, he enjoyed a twenty year research career at Bell Labs where he was a Department Head in Communications Systems Research. He has made fundamental contributions to digital signal processing, speech coding, and wireless information networks.
 A tutorial in each chapter on using MATLAB to understand and apply the theory introduced in the chapter.
 Material reorganized and expanded based on authors' teaching experience and feedback from students and instructors.
 Expanded coverage of applications of probability including estimation, hypothesis testing, and signal processing.
 A new chapter on random vectors.
 Coverage of Markov chains and elementary queuing theory made more accessible, with fewer preliminary details to absorb before reaching the subjects of greatest practical importance.
 Studentfriendly narrative aids intuitive understanding of realworld priciples underlying mathematical concepts. Motivates engineering students who often perceive the subject as abstract and irrelevant to their practical interests.
 MATLAB applications encourage students to gain handson experience with material presented in the text. Instructors have access to program files provided by the authors, and do not need to create and debug their own code.
 Extensive collection of exercises (examples, quizzes, and homework problems). Degree ofdifficulty of each homework problem clearly labeled. Assists students with the most difficult part of learning probability—going from theory to practical applications.
 Separate treatment of discrete and continuous random variables. Students, especially those encountering material for the first time, can learn basic principles without the confusion of two different ways of calculating probabilities and averages (sums and integrals). Seeing the same principles twice reinforces the learning experience.
 WWW support for instructors, especially including solutions to homework problems. Graphical interface enables instructors to generate customized solutions handouts and offers flexibility in the way homework problems are used. Saves instructor time in solving exercises and preparing information for students.
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