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Probability and Stochastic Processes 4/e IA+作者：
Yates+年份：
2025 年4 版
+ISBN：
9781394304226
+書號：
PS0517P
+規格：
平裝/單色
+頁數：
576
+出版商：
John Wiley
+參考資訊：
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定價
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●New and expanded coverage on topics including those on:。Sample Mean and Variance
。Markov Process
。Discrete-Time Markov Chains
。Higher Transition Probabilities: Chapman–Kolmogorov Equations
。Long-run Behavior of Markov Chains
。Classification of States of Chains
。Markov Chains with Countably Infinite States
。Ergodic and Reducible Chains
。Birth Process and Death Process
。Queuing Models – Poisson Queues
●A new Chapter on Stochastic processes and Markov chains introduces which includes some new topics:。Characteristic Function and Probability Generating Function” inserted
。Markov Inequality
。Chebyshev’s Inequality
。Chernoff Bound
●A Chapter on The Sample Mean now present in the Appendix as Appendix A.
●“Quiz” given at the end of each section to evaluate the understating of the concepts.
●“Definitions” given within the section such that, prompt students to recognize the important takeaways or concepts in each section, providing the scaffolding for understanding by better defining these important points.
●Examples questions appear at the end of every section and are designed for students to check their mastery of the section’s key concepts.
●Difficulty Levels of the Problems at the endof each chapter, problems have been tagged with the difficulty level for better testing to the readers.
Roy Yates received the B.S.E. degree in 1983 from Princeton and the S.M. and Ph.D. degrees in 1986 and 1990 from MIT, all in Electrical Engineering. Since 1990, he has been with the Wireless Information Networks Laboratory (WINLAB) and the ECE department at Rutgers University. Presently, he is an Associate Director of WINLAB and a Professor in the ECE Dept. He is a co-author (with David Goodman) of the text Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers, published by John Wiley and Sons. He is a co-recipient (with Christopher Rose and Sennur Ulukus) of the 2003 IEEE Marconi Prize Paper Award in Wireless Communications. His research interests include power control, interference suppression and spectrum regulation for wireless systems.
1 Random Experiments, Models, and Probabilities
2 Sequential Random Experiments
3 Discrete Random Variables
4 Continuous Random Variables
5 Multiple Random Variables
6 Probability Models of Derived Random Variables
7 Conditional Probability Models
8 Random Vectors
9 Sums of Random Variables
10 Hypothesis Testing
11 Estimation of a Random Variable
12 Some Probabilistic Inequalities and Bounds
13 Stochastic Processes and Markov Chains
14 Stationary Processes and Random Signal Processing
Appendix A The Sample Mean
Appendix B Families of Random Variables
Appendix C A Few Math Facts
