Probability in Electrical Engineering and Computer Science读书介绍

The book is designed for a junior/senior level course. Applications drive the material: PageRank, Multiplexing, Digital Link, Tracking, Speech Recognition, Route Planning and more. Topics include Markov chains, detection, coding, estimation, Viterbi algorithm, expectation maximization, clustering, compressed sensing, recommender systems, Kalman Filter, Markov decision problems, LQG, and channel capacity. Matlab examples are used to simulate models and to implement the algorithms. Appendices provide the necessary background in basic probability and linear algebra. See https://sites.google.com/site/walrandpeecs/home.

Jean Walrand received his Ph.D. in EECS from UC Berkeley and has been on the faculty of that department since 1982. He is the author of An Introduction to Queueing Networks (Prentice Hall, 1988) and of Communication Networks: A First Course (2nd ed. McGraw-Hill,1998) and co-author of High-Performance Communication Networks (2nd ed, Morgan Kaufman, 2000), of Communication Networ...

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