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.
Home page url
Download or read it online for free here:
(multiple PDF files)
by Javier Prieto Tejedor (ed.) - InTech
This book takes a look at both theoretical foundations and practical implementations of Bayesian inference. It is intended as an introductory guide for the application of Bayesian inference in the fields of life sciences, engineering, and economics.
by William A. Gardner - Prentice Hall
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.
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.
by Julius O. Smith III - DSPRelated.com
This book was developed for a course entitled 'Signal Processing Methods in Musical Acoustics'. The text was created primarily as a research preparation and dissemination vehicle intended for graduate students in computer music and engineering.