Probability in Electrical Engineering & Computer Science
An Application-Driven Course
This book is available for download with iBooks on your Mac or iOS device. Multi-touch books can be read with iBooks on your Mac or iOS device. Books with interactive features may work best on an iOS device. iBooks on your Mac requires OS X 10.9 or later.
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 is a Professor of Electrical Engineering and Computer Science at the University of California at Berkeley.
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Extraordinary Computer Science Book
This is a comprehensive and one of a kind science book every 21st century computer scientist must have. Wonderful!