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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Turbo Message Passing Algorithms for Structured Signal Recovery

Turbo Message Passing Algorithms for Structured Signal Recovery

Yuan, Xiaojun
Xue, Zhipeng

Paperback

Series: Springerbriefs in Computer Science

Technology & EngineeringNetworking

ISBN10: 3030547612
ISBN13: 9783030547615
Publisher: Springer Nature
Published: Oct 14 2020
Pages: 105
Weight: 0.39
Height: 0.25 Width: 6.14 Depth: 9.21
Language: English

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.

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