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More About This Textbook
Overview
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A text on concepts of probability and stochastic processes, presented as a series of building blocks clearly identified as either an axiom, definition, or theorem. Treatment follows a consistent model that begins with an experiment consisting of a procedure and observations, with separate chapters on discrete and continuous random variables. Includes worked examples, exercises, quizes, and solutions. Problems are graded. For use in a one-semester undergraduate course. Annotation c. by Book News, Inc., Portland, Or.Product Details
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Meet the Author
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.
Table of Contents
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.