Probability in Electrical Engineering and Computer Science: An Application-Driven Course
β Scribed by Jean Walrand
- Publisher
- Springer
- Year
- 2021
- Tongue
- English
- Leaves
- 401
- Edition
- 1st ed. 2021
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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.Β For ancillaries related to this book, includingΒ examples of Python demos and also Python labs used in Berkeley, please email Mary James atΒ [email protected].
This is an open access book.Β
π SIMILAR VOLUMES
Written in a clear and concise style, this introduction to probability and random variables for junior and senior electrical and computer engineering undergraduates features applications and examples useful in other branches of engineering as well. Chapters focus on the probability model, random var
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