AMP-Inspired Deep Networks for Sparse Linear Inverse Problems

Deep learning has gained great popularity due to its widespread success on many inference problems. We consider the application of deep learning to the sparse linear inverse problem, where one seeks to recover a sparse signal from a few noisy linear measurements. In this paper, we propose two novel...

Full description

Bibliographic Details

Published in:	IEEE transactions on signal processing Vol. 65; no. 16; pp. 4293 - 4308
Main Authors:	Borgerding, Mark, Schniter, Philip, Rangan, Sundeep
Format:	Journal Article
Language:	English
Published:	IEEE 15.08.2017
Subjects:	approximate message passing Approximation algorithms compressive sensing Deep learning Inverse problems Machine learning massive MIMO Message passing Probability density function random access Signal processing algorithms Transforms
ISSN:	1053-587X, 1941-0476
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!