Turbo Message Passing Algorithms for Structured Signal Recovery / by Xiaojun Yuan, Zhipeng Xue.
2020
TK1-9971
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Details
Title
Turbo Message Passing Algorithms for Structured Signal Recovery / by Xiaojun Yuan, Zhipeng Xue.
Author
Yuan, Xiaojun. author.
Edition
1st ed. 2020.
ISBN
3030547620
9783030547622
3030547612
9783030547615
9783030547622
3030547612
9783030547615
Published
Cham : Springer International Publishing : Imprint: Springer, 2020.
Language
English
Description
1 online resource (XI, 105 pages) : illustrations.
Item Number
10.1007/978-3-030-54762-2 doi
Call Number
TK1-9971
Dewey Decimal Classification
621.382
Summary
This book takes a comprehensive study on turbo message passing algorithms for structured signal recovery, where the considered structured signals include 1) a sparse vector/matrix (which corresponds to the compressed sensing (CS) problem), 2) a low-rank matrix (which corresponds to the affine rank minimization (ARM) problem), 3) a mixture of a sparse matrix and a low-rank matrix (which corresponds to the robust principal component analysis (RPCA) problem). The book is divided into three parts. First, the authors introduce a turbo message passing algorithm termed denoising-based Turbo-CS (D-Turbo-CS). Second, the authors introduce a turbo message passing (TMP) algorithm for solving the ARM problem. Third, the authors introduce a TMP algorithm for solving the RPCA problem which aims to recover a low-rank matrix and a sparse matrix from their compressed mixture. With this book, we wish to spur new researches on applying message passing to various inference problems. Provides an in depth look into turbo message passing algorithms for structured signal recovery Includes efficient iterative algorithmic solutions for inference, optimization, and satisfaction problems through message passing Shows applications in areas such as wireless communications and computer vision.
Access Note
Access limited to authorized users.
Added Author
Xue, Zhipeng. author.
Series
SpringerBriefs in computer science, 2191-5768
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Table of Contents
Introduction
Turbo Message Passing for Compressed Sensing
Turbo Message Passing for Affine Rank Minimization
Turbo Message Passing for Compressed Robust Principal Component Analysis
Learned Turbo Message Passing Algorithms
Future Research Directions
Conclusion.
Turbo Message Passing for Compressed Sensing
Turbo Message Passing for Affine Rank Minimization
Turbo Message Passing for Compressed Robust Principal Component Analysis
Learned Turbo Message Passing Algorithms
Future Research Directions
Conclusion.