Probability in Electrical Engineering and Computer Science - An Application-Driven Course (Hardcover, 1st ed. 2021)

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. For ancillaries related to this book, including examples of Python demos and also Python labs used in Berkeley, please email Mary James at [email protected]. This is an open access book.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Release date:	June 2021
First published:	2021
Authors:	Jean Walrand
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	380
Edition:	1st ed. 2021
ISBN-13:	978-3-03-049994-5
Languages:	English
Subtitles:	English
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General
LSN:	3-03-049994-4
Barcode:	9783030499945

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