About Us

Math shortcuts, Articles, worksheets, Exam tips, Question, Answers, FSc, BSc, MSc

More about us

Keep Connect with Us

  • =

Login to Your Account

Probability in Electrical Engineering & Computer Science by Jean Walrand




Probability in Electrical Engineering & Computer Science by Jean Walrand - Table of Contents

1. PageRank: A 2. PageRank: B 3. Multiplexing: A 4. Multiplexing: B 5. Networks: A 6. Networks: B 7. Digital Link: A 8. Digital Link: B 9. Tracking: A 10. Tracking: B 11. Speech Recognition: A 12. Speech Recognition: B 13. Route Planning: A 14. Route Planning: B 15. Perspective and Complements A. Elementary Probability B. Basic Probability

What You Will Learn in Probability in Electrical Engineering & Computer Science by Jean Walrand

"Probability in Electrical Engineering and Computer Science: An Application-Driven Course" by Jean Camille Walrand is a practical and rigorous introduction to "probability theory" with applications in "electrical engineering" and "computer science". The book begins with foundational concepts such as "random variables", probability rules, and basic "distributions", making complex ideas accessible for students and professionals. Walrand emphasizes both intuition and formal reasoning to ensure a deep understanding of probabilistic principles. The text progresses to cover expectation, variance, conditional probability, and stochastic processes, including "Markov chains". Real-world examples and exercises are provided throughout, illustrating how probability is applied to communication systems, network modeling, signal processing, and algorithm analysis. Each concept is carefully explained to show how mathematical theory translates into practical engineering and computing solutions. Highly regarded for its clarity and applied focus, "Probability in Electrical Engineering & Computer Science" equips readers with the tools to analyze uncertainty, model random systems, and design solutions based on probabilistic reasoning. Its combination of theory, applications, and exercises makes it suitable for undergraduate and graduate courses, self-study, or professional reference in "stochastic modeling" and applied probability. The book provides a solid foundation for further study in probabilistic methods and systems engineering.

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 an American mathematician and engineer who earned his "Ph.D. in Electrical Engineering and Computer Sciences from UC?Berkeley". He has spent most of his career at "Berkeley’s EECS department", focusing on applied probability and mathematical modeling in engineering systems. Walrand is an expert in "stochastic processes", "queuing theory", and "communication networks". He authored textbooks such as "Probability in Electrical Engineering & Computer Science", which blend theory with practical applications. His work bridges mathematics and engineering, helping students and professionals apply probabilistic methods to real-world systems, making him a recognized leader in "applied probability" and network modeling.

Free Stochastic Processes Books PDF | Probability Theory Resources

Stochastic Calculus with Finance Applications - Kozdron
Explore Financial Derivatives, Stochastic Calculus, and market modeling with Michael Kozdron’s easy-to-understand finance mathematics book.
Essentials of Stochastic Processes - Rick Durrett
Master stochastic processes with Rick Durrett’s essential text, covering probability theory, modeling, and applied math in clear, practical examples.
Stochastic Processes & Mathematics of Finance - J.Block
Learn how stochastic processes and probability theory are used in finance. J. Block explains Brownian motion, martingales, and option pricing models.
Basic Probability Theory - Robert B. Ash
Learn core probability, random variables, and distributions with Robert B. Ash’s clear guide for students and self-learners.
Random Graphs & Complex Networks - R. van der Hofstad
Learn Random Graphs and Complex Networks with Remco van der Hofstad’s guide to graph theory, network modeling, and real-world applications.

Mathematics Book Categories

.