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Probability in Electrical Engineering and Computer Science : An Application-Driven Course (1st ed. 2020)

By: Walrand, Jean

3030499944 / 9783030499945
Hardback
10/10/2020
Published 10/10/2020
Switzerland
155 x 235 mm 376 pages, 150 Tables, color; 145 Illustrations, color; 69 Illustrations, black and white; XXI, 376
Professional & Vocational  Learn More

This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering and computer science (EECS).

The author presents information processing and communication systems that use algorithms based on probabilistic models and techniques, including web searches, digital links, speech recognition, GPS, route planning, recommendation systems, classification, and estimation.

He then explains how these applications work and, along the way, provides the readers with the understanding of the key concepts and methods of applied probability.

Python labs enable the readers to experiment and consolidate their understanding.

The book includes homework, solutions, and Jupyter notebooks.

This edition includes new topics such as Boosting, Multi-armed bandits, statistical tests, social networks, queuing networks, and neural networks.

The companion website now has many examples of Python demos and also Python labs used in Berkeley.

BIC:

PBT Probability & statistics, TBJ Maths for engineers, TJK Communications engineering / telecommunications, UYAM Maths for computer scientists

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