Hidden Markov Models: Estimation and Control
by R. J. Elliott, L. Aggoun, J. B. Moore
Publisher: Springer 1995
Number of pages: 373
The aim of this book is to present graduate students with a thorough survey of reference probability models and their applications to optimal estimation and control. These new and powerful methods are particularly useful in signal processing applications where signal models are only partially known and are in noisy environments.
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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 Sergio Rui Silva - InTech
Simulation and 3D reconstruction of side-looking sonar images, synthetic aperture techniques, ensemble averaging and resolution enhancement of digital radar and sonar signals, multi-sonar integration and the advent of sensor intelligence, and more.
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 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.