Sparse Optimization Theory And Methods

Download Sparse Optimization Theory And Methods full books in PDF, epub, and Kindle. Read online free Sparse Optimization Theory And Methods ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Sparse Optimization Theory and Methods

Sparse Optimization Theory and Methods
Author :
Publisher : CRC Press
Total Pages : 297
Release :
ISBN-10 : 9781351624152
ISBN-13 : 1351624156
Rating : 4/5 (156 Downloads)

Book Synopsis Sparse Optimization Theory and Methods by : Yun-Bin Zhao

Download or read book Sparse Optimization Theory and Methods written by Yun-Bin Zhao and published by CRC Press. This book was released on 2018-07-04 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seeking sparse solutions of underdetermined linear systems is required in many areas of engineering and science such as signal and image processing. The efficient sparse representation becomes central in various big or high-dimensional data processing, yielding fruitful theoretical and realistic results in these fields. The mathematical optimization plays a fundamentally important role in the development of these results and acts as the mainstream numerical algorithms for the sparsity-seeking problems arising from big-data processing, compressed sensing, statistical learning, computer vision, and so on. This has attracted the interest of many researchers at the interface of engineering, mathematics and computer science. Sparse Optimization Theory and Methods presents the state of the art in theory and algorithms for signal recovery under the sparsity assumption. The up-to-date uniqueness conditions for the sparsest solution of underdertemined linear systems are described. The results for sparse signal recovery under the matrix property called range space property (RSP) are introduced, which is a deep and mild condition for the sparse signal to be recovered by convex optimization methods. This framework is generalized to 1-bit compressed sensing, leading to a novel sign recovery theory in this area. Two efficient sparsity-seeking algorithms, reweighted l1-minimization in primal space and the algorithm based on complementary slackness property, are presented. The theoretical efficiency of these algorithms is rigorously analysed in this book. Under the RSP assumption, the author also provides a novel and unified stability analysis for several popular optimization methods for sparse signal recovery, including l1-mininization, Dantzig selector and LASSO. This book incorporates recent development and the author’s latest research in the field that have not appeared in other books.


Sparse Optimization Theory and Methods Related Books

Sparse Optimization Theory and Methods
Language: en
Pages: 222
Authors: Yun-Bin Zhao
Categories: Business & Economics
Type: BOOK - Published: 2018-07-04 - Publisher: CRC Press

DOWNLOAD EBOOK

Seeking sparse solutions of underdetermined linear systems is required in many areas of engineering and science such as signal and image processing. The efficie
Sparsity Methods for Systems and Control
Language: en
Pages: 220
Authors: Masaaki Nagahara
Categories:
Type: BOOK - Published: 2020-09-30 - Publisher:

DOWNLOAD EBOOK

The method of sparsity has been attracting a lot of attention in the fields related not only to signal processing, machine learning, and statistics, but also sy
Sparse Modeling
Language: en
Pages: 255
Authors: Irina Rish
Categories: Business & Economics
Type: BOOK - Published: 2014-12-01 - Publisher: CRC Press

DOWNLOAD EBOOK

Sparse models are particularly useful in scientific applications, such as biomarker discovery in genetic or neuroimaging data, where the interpretability of a p
Direct Methods for Sparse Linear Systems
Language: en
Pages: 228
Authors: Timothy A. Davis
Categories: Computers
Type: BOOK - Published: 2006-09-01 - Publisher: SIAM

DOWNLOAD EBOOK

The sparse backslash book. Everything you wanted to know but never dared to ask about modern direct linear solvers. Chen Greif, Assistant Professor, Department
Iterative Methods for Sparse Linear Systems
Language: en
Pages: 537
Authors: Yousef Saad
Categories: Mathematics
Type: BOOK - Published: 2003-04-01 - Publisher: SIAM

DOWNLOAD EBOOK

Mathematics of Computing -- General.