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 Julius O. Smith III - W3K Publishing
An introduction to digital filters, it covers mathematical theory, useful examples, audio applications, and some software starting points and Matlab programming examples. The theory treats concepts in digital filter analysis and linear systems theory.
by Allen B. Downey - Green Tea Press
'Think DSP: Digital Signal Processing in Python' is an introduction to signal processing and system analysis using a computational approach. The premise of this book is that if you know how to program, you can use that skill to learn other things.
by Fausto Pedro García Marquez - InTech
Digital filters are the most versatile, practical and effective methods for extracting the information necessary from the signal. This book presents the most advanced digital filters including different case studies and the most relevant literature.
by 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.