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Probability in Electrical Engineering and Computer Science (EECS)
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  • Title Probability in Electrical Engineering and Computer Science: An Application-Driven Course
  • Author(s) Jean Camille Walrand
  • Publisher: Springer; 1st ed. 2021 edition (June 23, 2021); eBook (Open Access Edition)
  • License(s): CC BY 4.0
  • Hardcover 401 pages
  • eBook PDF (389 pages) and ePub
  • Language: English
  • ISBN-10/ASIN: 3030499944
  • ISBN-13: 978-3030499945
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Book Description

This 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.

  • Showcases techniques of applied probability with applications in EE and CS;
  • Presents all topics with concrete applications so students see the relevance of the theory;
  • Illustrates methods with Jupyter notebooks that use widgets to enable the users to modify parameters.
About the Authors
  • Jean Camille Walrand is a professor emeritus of Electrical Engineering and Computer Science at UC Berkeley. He is a Fellow of the Belgian American Education Foundation and of the IEEE. Additionally, he is a recipient of the Lanchester Prize, the Stephen O. Rice Prize., the IEEE Kobayashi Award, and the ACM SIGMETRICS Achievement Award.
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