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ICASSP
2009
IEEE

Sparse Decomposition over non-full-rank dictionaries

10 years 4 months ago
Sparse Decomposition over non-full-rank dictionaries
Sparse Decomposition (SD) of a signal on an overcomplete dictionary has recently attracted a lot of interest in signal processing and statistics, because of its potential application in many different areas including Compressive Sensing (CS). However, in the current literature, the dictionary matrix has generally been assumed to be of full-rank. In this paper, we consider non-full-rank dictionaries (which are not even necessarily overcomplete), and extend the definition of SD over these dictionaries. Moreover, we present an approach which enables to use previously developed SD algorithms for this non-full-rankcase. Besides this general approach, for the special case of the Smoothed ¥¢¦ (SL0) algorithm, we show that a slight modification of it covers automatically non-full-rank dictionaries.
Massoud Babaie-Zadeh, Vincent Vigneron, Christian
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where ICASSP
Authors Massoud Babaie-Zadeh, Vincent Vigneron, Christian Jutten
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