An Introduction to Statistical Signal Processing by Gray & Davisson
An Introduction to Statistical Signal Processing - Table of Contents
1. Introduction
2. Probability
3. Random Variables, Vectors, and Processes
4. Expectation and Averages
5. Second-Order Theory
6. A Menagerie of Processes
A. Preliminaries
B. Sums and Integrals
C. Common Univariate Distributions
D. Supplementary Reading
What You Will Learn in An Introduction to Statistical Signal Processing
"An Introduction to Statistical Signal Processing" by Robert M. Gray and Lee D. Davisson is a foundational textbook that explains how to analyze and model signals using probability. The book focuses on "statistical signal processing", helping readers understand how randomness affects real-world signals like noise and communication data. It blends theory with practical insight, making complex ideas easier to follow.
The content covers essential topics such as "random processes", "probability theory", and "correlation analysis". It teaches how to represent signals mathematically and apply these concepts in systems like communications and data transmission. With clear explanations and structured examples, it builds a strong base for students and engineers working in electrical engineering and applied mathematics.
This book is highly recommended for graduate-level learners and professionals who want to master "signal processing" concepts. Its balanced approach between theory and application makes it a valuable resource for understanding modern communication systems. Overall, it remains a trusted guide for anyone looking to develop deep knowledge in "stochastic modeling" and advanced signal analysis.
Book Details & Specifications
Title:
An Introduction to Statistical Signal Processing by Gray & Davisson
Publisher:
Cambridge University Press
Year:
2011
Pages:
475
Type:
PDF
Language:
English
ISBN-10 #:
0521131820
ISBN-13 #:
978-0521131827
License:
External Educational Resource
Amazon:
Amazon
About the Author: Robert M. Gray and Lee D. Davisson
The author
Robert M. Gray and Lee D. Davisson
are the two respected experts in "statistical signal processing". Gray studied Electrical Engineering at MIT and earned his Ph.D. from USC, later becoming a professor at Stanford. His work focuses on "information theory", signal analysis, and data modeling. Davisson completed his Ph.D. at Princeton University and taught at the University of Maryland. His expertise includes "communication systems", coding theory, and probability. Together, they created a strong foundation for understanding "random processes" and modern signal analysis.
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