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134
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CORR
2007
Springer
136views Education» more  CORR 2007»
15 years 3 months ago
Sparsity in time-frequency representations
We consider signals and operators in finite dimension which have sparse time-frequency representations. As main result we show that an S-sparse Gabor representation in Cn with re...
Götz E. Pfander, Holger Rauhut
INTERSPEECH
2010
14 years 10 months ago
Artificial and online acquired noise dictionaries for noise robust ASR
Recent research has shown that speech can be sparsely represented using a dictionary of speech segments spanning multiple frames, exemplars, and that such a sparse representation ...
Jort F. Gemmeke, Tuomas Virtanen
172
Voted
CORR
2012
Springer
225views Education» more  CORR 2012»
13 years 11 months ago
Compressive Principal Component Pursuit
We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in co...
John Wright, Arvind Ganesh, Kerui Min, Yi Ma
CORR
2011
Springer
210views Education» more  CORR 2011»
14 years 10 months ago
Statistical Compressed Sensing of Gaussian Mixture Models
A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribu...
Guoshen Yu, Guillermo Sapiro
ICASSP
2011
IEEE
14 years 7 months ago
Using the kernel trick in compressive sensing: Accurate signal recovery from fewer measurements
Compressive sensing accurately reconstructs a signal that is sparse in some basis from measurements, generally consisting of the signal’s inner products with Gaussian random vec...
Hanchao Qi, Shannon Hughes