Logo

Statistical Spectral Analysis: A Non-Probabilistic Theory

Large book cover: Statistical Spectral Analysis: A Non-Probabilistic Theory

Statistical Spectral Analysis: A Non-Probabilistic Theory
by

Publisher: Prentice Hall
ISBN/ASIN: 0138445729
ISBN-13: 9780138445720
Number of pages: 591

Description:
This book is intended to serve as both a graduate-level textbook and a technical reference. The focus is on fundamental concepts, analytical techniques, and basic empirical methods. The only prerequisite is an introductory course on Fourier analysis.

Home page url

Download or read it online for free here:
Download link
(41MB, PDF)

Similar books

Book cover: Optimal FilteringOptimal Filtering
by - Prentice-Hall
This graduate-level text augments and extends studies of signal processing, particularly in regard to communication systems and digital filtering theory. Topics include filtering, linear systems, and estimation; the discrete-time Kalman filter; etc.
(19478 views)
Book cover: Fourier Transform - Signal ProcessingFourier Transform - Signal Processing
by - InTech
This book focuses on the Fourier transform applications in signal processing techniques. Topics covered: DFT, FFT, OFDM, estimation techniques and the image processing techniques. Written for electrical engineers, communication engineers, etc.
(10827 views)
Book cover: An Introduction to Statistical Signal ProcessingAn Introduction to Statistical Signal Processing
by - Cambridge University Press
The book covers basic probability, random objects, expectation, second order moment theory with examples of the random process models and their basic properties, specific applications for communication, estimation, detection, modulation.
(24789 views)
Book cover: Modern Signal ProcessingModern Signal Processing
by - Cambridge University Press
The book about the mathematical basis of signal processing and its many areas of application for graduate students. The text emphasizes current challenges, new techniques adapted to new technologies, and recent advances in algorithms and theory.
(17254 views)