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.
Download or read it online for free here:
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 Walt Kester - Newnes
The book explains signal processing hardware. It covers sampled data systems, A-to-D and D-to-A converters for DSP applications, fast Fourier transforms, digital filters, DSP hardware, interfacing to DSP chips, hardware design techniques.
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 Salih Mohammed Salih (ed.) - InTech
The book covers fast hybrid recursive FT based on Jacket matrix, acquisition algorithm for global navigation system, determining the sensitivity of output parameters based on FFT, convergence of integrals based on Riemann-Lebesgue Lemma function, ...