Knowledge-Aided Normalized Iterative Hard Thresholding Algorithms for Sparse Recovery

This paper deals with the problem of sparse recovery often found in compressive sensing applications exploiting a priori knowledge. In particular, we present a knowledge-aided normalized iterative hard thresholding (KA-NIHT) algorithm that exploits information about the probabilities of nonzero entr...

Celý popis

Podrobná bibliografia

Vydané v:	2018 26th European Signal Processing Conference (EUSIPCO) s. 1965 - 1969
Hlavní autori:	Jiang, Qianru, de Lamare, Rodrigo C., Zakharov, Yuriy, Li, Sheng, He, Xiongxiong
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	EURASIP 01.09.2018
Predmet:	Compressed sensing Europe Iterative algorithms iterative hard thresholding Matching pursuit algorithms prior information probability estimation Signal processing Signal processing algorithms Simulation sparse recovery
ISSN:	2076-1465
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!