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...

Celý popis

Podrobná bibliografia

Vydané v:	IEEE transactions on signal processing Ročník 65; číslo 16; s. 4293 - 4308
Hlavní autori:	Borgerding, Mark, Schniter, Philip, Rangan, Sundeep
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 15.08.2017
Predmet:	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
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!