Modern Signal Processing
by Daniel N. Rockmore, Jr, Dennis M. Healy
Publisher: Cambridge University Press 2004
Number of pages: 352
The mathematical basis of signal processing and its many areas of application is the subject of this book. Based on a series of graduate-level lectures held at the Mathematical Sciences Research Institute, the volume emphasizes current challenges, new techniques adapted to new technologies, and certain recent advances in algorithms and theory.
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by John C. Nash - Marcel Dekker Inc
This book and software collection is intended to help scientists, engineers and statisticians in their work. We have collected various software tools for nonlinear parameter estimation, along with representative example problems.
by Julius O. Smith III - W3K Publishing
Detailed mathematical derivation of DFT (Discrete Fourier Transform), with elementary applications to audio signal processing. Matlab programming examples are included. High-school math background is a prerequisite, including some calculus.
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.
by 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.