Probability in Electrical Engineering and Computer Science by Jean Walrand
Probability in Electrical Engineering and Computer Science - Table of Contents
- PART I: BASIC PROBABILITY & RANDOM VARIABLES
- 1. Probability Space and Events
- 2. Conditional Probability and Independence
- 3. Discrete Random Variables
- 4. Continuous Random Variables
- 5. Jointly Distributed Random Variables
- 6. Expectations and Limit Theorems
- PART II: STOCHASTIC PROCESSES & MARKOV MODELS
- 7. Discrete-Time Markov Chains
- 8. Continuous-Time Markov Chains
- 9. The Poisson Process and Renewal Theory
- PART III: APPLICATIONS IN NETWORKS & INFERENCE
- 10. Queueing Theory and System Performance
- 11. Detection and Bayesian Inference Techniques
- 12. Estimation and LMS Techniques
- 13. Probabilistic Models in Machine Learning
- 14. Information Theory and Coding Fundamentals
- 15. Random Graphs and Complex Networks
What You Will Learn in Probability in Electrical Engineering and Computer Science
Probability in Electrical Engineering and Computer Science: An Application-Driven Course by Jean Walrand delivers a rigorous yet highly accessible introduction to probability theory tailored specifically for technical disciplines. Bridging fundamental mathematical abstractions with real-world technological applications, this text breaks down core concepts including discrete and continuous random variables, Markov chains, Poisson processes, queueing systems, Bayesian inference, and detection theory into clear, well-structured lessons.
Designed for undergraduate and graduate engineering students, computer scientists, network architects, and system analysts, this book demonstrates how probabilistic tools model complex real-world dynamics. Prof. Walrand guides readers through practical engineering challenges, such as communication link design, packet-switched routing performance, page-ranking algorithms, machine learning classification, and resource allocation in cloud computing environments.
Highly appreciated for its clear pedagogical layout, practical motivation, and integration of modern computing topics, it stands as one of the best applied probability textbooks pdf available for independent study. It systematically equips learners with necessary quantitative tools for mastering stochastic systems and engineering modeling with confidence.
Book Details & Specifications
Title:
Probability in Electrical Engineering and Computer Science by Jean Walrand
Publisher:
Springer
Year:
2022
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 a Professor Emeritus of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. He earned his Ph.D. in Electrical Engineering from the University of Illinois, Urbana-Champaign, and is an IEEE Fellow.
A leading authority in stochastic processes and communication networks, Prof. Walrand has authored several seminal textbooks on computer networking, queueing systems, and probability. His research focuses on network architecture, wireless communication, pricing models, and performance evaluation of complex interconnected systems.
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