An Introduction to Sparse Stochastic Processes (Hardcover)

Providing a novel approach to sparse stochastic processes, this comprehensive book presents the theory of stochastic processes that are ruled by stochastic differential equations, and that admit a parsimonious representation in a matched wavelet-like basis. Two key themes are the statistical property of infinite divisibility, which leads to two distinct types of behaviour - Gaussian and sparse - and the structural link between linear stochastic processes and spline functions, which is exploited to simplify the mathematical analysis. The core of the book is devoted to investigating sparse processes, including a complete description of their transform-domain statistics. The final part develops practical signal-processing algorithms that are based on these models, with special emphasis on biomedical image reconstruction. This is an ideal reference for graduate students and researchers with an interest in signal/image processing, compressed sensing, approximation theory, machine learning, or statistics.

General

Imprint:	Cambridge UniversityPress
Country of origin:	United Kingdom
Release date:	August 2014
Authors:	Michael Unser • Pouya D. Tafti
Dimensions:	253 x 179 x 20mm (L x W x T)
Format:	Hardcover
Pages:	384
ISBN-13:	978-1-107-05854-5
Categories:	Books > Science & Mathematics > Mathematics > Applied mathematics > Stochastics Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
LSN:	1-107-05854-6
Barcode:	9781107058545

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