DocumentCode :
179067
Title :
Compressed sensing for block-sparse smooth signals
Author :
Gishkori, Shahzad ; Leus, Geert
Author_Institution :
Fac. of EEMCS, Delft Univ. of Technol., Delft, Netherlands
fYear :
2014
fDate :
4-9 May 2014
Firstpage :
4166
Lastpage :
4170
Abstract :
We present reconstruction algorithms for smooth signals with block sparsity from their compressed measurements. We tackle the issue of varying group size via the group-sparse least absolute shrinkage selection operator (LASSO) as well as via latent group LASSO regularizations. We achieve smoothness in the signal via fusion. We develop low-complexity solvers for our proposed formulations through the alternating direction method of multipliers.
Keywords :
compressed sensing; signal reconstruction; smoothing methods; alternating direction method of multipliers; block-sparse smooth signals; compressed measurements; compressed sensing; group size; group-sparse least absolute shrinkage selection operator; latent group LASSO regularizations; low-complexity solvers; signal via fusion; smooth signal reconstruction algorithms; Compressed sensing; Convergence; Optimization; Signal reconstruction; System-on-chip; Vectors; Compressed sensing; block sparsity; signal reconstruction; smoothness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location :
Florence
Type :
conf
DOI :
10.1109/ICASSP.2014.6854386
Filename :
6854386
Link To Document :
بازگشت