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» On sparse signal representations
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IJON
2008
116views more  IJON 2008»
14 years 11 months ago
Discovering speech phones using convolutive non-negative matrix factorisation with a sparseness constraint
Discovering a representation that allows auditory data to be parsimoniously represented is useful for many machine learning and signal processing tasks. Such a representation can ...
Paul D. O'Grady, Barak A. Pearlmutter
ICASSP
2010
IEEE
15 years 7 hour ago
A weighted discriminative approach for image denoising with overcomplete representations
We present a novel weighted approach for shrinkage functions learning in image denoising. The proposed approach optimizes the shape of the shrinkage functions and maximizes denois...
Amir Adler, Yacov Hel-Or, Michael Elad
INTERSPEECH
2010
14 years 6 months ago
Sparse component analysis for speech recognition in multi-speaker environment
Sparse Component Analysis is a relatively young technique that relies upon a representation of signal occupying only a small part of a larger space. Mixtures of sparse components ...
Afsaneh Asaei, Hervé Bourlard, Philip N. Ga...
ICASSP
2011
IEEE
14 years 3 months ago
Bayesian framework and message passing for joint support and signal recovery of approximately sparse signals
In this paper, we develop a low-complexity message passing algorithm for joint support and signal recovery of approximately sparse signals. The problem of recovery of strictly spa...
Shubha Shedthikere, Ananthanarayanan Chockalingam
ICIP
2005
IEEE
16 years 1 months ago
The M-term pursuit for image representation and progressive compression
This paper introduces a sparse signal representation algorithm in redundant dictionaries, called the M-Term Pursuit (MTP), with an application to image representation and scalable ...
Adel Rahmoune, Pierre Vandergheynst, Pascal Frossa...