Introduction to Sparse Stochastic Processes - Info and Reading Options
By Michael Unser and Pouya D. Tafti
"Introduction to Sparse Stochastic Processes" was published by University of Cambridge ESOL Examinations in 2014 - Cambridge, it has 387 pages and the language of the book is English.
“Introduction to Sparse Stochastic Processes” Metadata:
- Title: ➤ Introduction to Sparse Stochastic Processes
- Authors: Michael UnserPouya D. Tafti
- Language: English
- Number of Pages: 387
- Publisher: ➤ University of Cambridge ESOL Examinations
- Publish Date: 2014
- Publish Location: Cambridge
“Introduction to Sparse Stochastic Processes” Subjects and Themes:
- Subjects: Random fields - Gaussian processes - Differential equations - Stochastic differential equations
Edition Identifiers:
- The Open Library ID: OL29258668M - OL21076801W
- ISBN-13: 9781107415805
- All ISBNs: 9781107415805
AI-generated Review of “Introduction to Sparse Stochastic Processes”:
"Introduction to Sparse Stochastic Processes" Description:
Open Data:
Providing a novel approach to sparsity, this comprehensive book presents the theory of stochastic processes that are ruled by linear 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
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