Ebook: Turbo Message Passing Algorithms for Structured Signal Recovery
Author: Xiaojun Yuan Zhipeng Xue
- Tags: Engineering, Communications Engineering Networks, Signal Image and Speech Processing, Computer Communication Networks
- Series: SpringerBriefs in Computer Science
- Year: 2020
- Publisher: Springer International Publishing
- Edition: 1st ed.
- Language: English
- pdf
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