An Introduction to Statistical Signal Processing
by R. M. Gray, L. D. Davisson
Publisher: Cambridge University Press 2005
ISBN/ASIN: 0521838606
ISBN-13: 9780521838603
Number of pages: 478
Description:
This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to specific applications in communications and signal processing. The book begins with a development of basic probability, random objects, expectation, and second order moment theory followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the book.
Download or read it online for free here:
Download link
(2.9MB, PDF)
Similar books
The Fourier Transform and its Applicationsby Brad Osgood - Stanford University
This text is appropriate for science and engineering students. Topics include: Periodicity and Fourier series; The Fourier transform and its basic properties; Convolution and its applications; Distributions and their Fourier transforms; etc.
(21195 views)
An Exploration of Random Processes for Engineersby Bruce Hajek - University of Illinois at Urbana-Champaign
These notes were written for a graduate course on random processes. Students are assumed to have had a previous course in probability, some familiarity with real analysis and linear algebra, and some familiarity with complex analysis.
(17875 views)
Fourier Transforms: High-tech Application and Current Trendsby G. Nikolic, M. Cakic, D. Cvetkovic (eds) - InTech
The book provides a review on recent advances in Fourier transforms as the most powerful analytical tool for applications in electronic and computer engineering, as well as spectral techniques with a wide range of nanotechnological applications.
(8722 views)
R. R. Bahadur's Lectures on the Theory of Estimationby Raghu Raj Bahadur, at al. - IMS
In this volume the author covered what should be standard topics in a course of parametric estimation: Bayes estimates, unbiased estimation, Fisher information, Cramer-Rao bounds, and the theory of maximum likelihood estimation.
(13237 views)