Statistical Spectral Analysis: A Non-Probabilistic Theory
by William A. Gardner
Publisher: Prentice Hall 1988
Number of pages: 591
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.
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by Jeff Fessler - University of Michigan
Course objectives: 1. to teach students the concepts of discrete-time signals, including mathematical representations; 2. to teach students the concepts of linear time-invariant discrete-time systems; 3. to introduce the concepts of filter design.
by 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.
by John Treichler - Connexions
This book examines how to convert a typical filter specification into a reasonably accurate estimate of the length of the impulse response. The text covers filter sizing, performance comparisons with other FIR design methods, etc.
by Daniel N. Rockmore, Jr, Dennis M. Healy - 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.