Probability in Electrical Engineering & Computer Science by Jean Walrand
Probability in Electrical Engineering & Computer Science - Table of Contents
- 1. Basic Probability
- 2. Random Variables and Expectation
- 3. Discrete-Time Markov Chains
- 4. Continuous-Time Markov Chains & Queueing
- 5. Bounds and Limit Theorems
- 6. Detection and Estimation Theory
- 7. Information Theory and Coding
- 8. Machine Learning and Data Analytics
- 9. Dynamic Programming and Control
What You Will Learn in Probability in Electrical Engineering & Computer Science
Probability in Electrical Engineering & Computer Science by Jean Walrand is an acclaimed university-level textbook designed to connect rigorous probabilistic reasoning directly to modern technology systems. This modern text breaks down complex topics like Markov chains, Poisson processes, detection theory, and PageRank algorithms into accessible, intuitive derivations. Designed for upper-level undergraduate and graduate students, it replaces dry abstract theory with interactive computational intuition.
Perfect for students and researchers in electrical engineering, computer science, data science, and network engineering, this textbook develops foundational theory alongside modern engineering applications. Walrand explains core concepts using engaging language, Python and MATLAB code snippets, and real-world case studies spanning computer networks, machine learning algorithms, and signal processing. Whether you are analyzing cloud server queueing delays or building probabilistic models for modern data processing, this book provides a step-by-step framework through every chapter.
Known globally for its clarity, practical relevance, and student-friendly approach, it remains one of the best probability for computer science books pdf available. It balances mathematical precision with engineering practice, making it an essential resource for mastering probabilistic system analysis with confidence.
Book Details & Specifications
Title:
Probability in Electrical Engineering & Computer Science by Jean Walrand
Publisher:
Springer
Year:
2021
Pages:
391
Type:
PDF
Language:
English
ISBN-10 #:
0615899366
ISBN-13 #:
978-0615899367
License:
CC BY 4.0
Amazon:
Amazon
About the Author: Jean Camille Walrand
The author Jean Camille Walrand
is Professor Emeritus of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. He received his Ph.D. from the University of Illinois, Urbana-Champaign, and is an IEEE Fellow as well as a recipient of the prestigious IEEE Koji Kobayashi Computers and Communications Award.
Renowned worldwide for his pioneering research in communication networks, stochastic control, and queueing theory, Walrand has authored several influential textbooks in engineering and applied mathematics. His work on probability theory and computer systems modeling equips students and industry practitioners with clear, computationally grounded tools for analyzing complex quantitative systems.
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