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Probability and Stochastic Processes
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Table of Contents

Features of this Text. 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.

About the Author

Dr. Roy Yates received the B.S.E. degree in 1983 from Princeton University, and the S.M. and Ph.D. degrees in 1986 and 1990 from M.I.T., all in Electrical Engineering. Since 1990, he has been with the Wireless Information Networks Laboratory (WINLAB) and the ECE department at Rutgers, University. He is currently an associate professor. 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.

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