Turbo Message Passing Algorithms for Structured Signal Recovery (Paperback, 1st ed. 2020)

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

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Computer Science
Release date:	October 2020
First published:	2020
Authors:	Xiaojun Yuan • Zhipeng Xue
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	105
Edition:	1st ed. 2020
ISBN-13:	978-3-03-054761-5
Categories:	Books > Computing & IT > Internet > Network computers Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General Promotions
LSN:	3-03-054761-2
Barcode:	9783030547615

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