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» Compressive sensing for sparsely excited speech signals
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TIT
2010
174views Education» more  TIT 2010»
15 years 21 days ago
Toeplitz Compressed Sensing Matrices With Applications to Sparse Channel Estimation
Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. In essence, CS enables the recovery of high-dimensional sparse signals from relatively few ...
Jarvis Haupt, Waheed Uz Zaman Bajwa, Gil M. Raz, R...
ICASSP
2008
IEEE
16 years 13 days ago
Compressed sensing with sequential observations
Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of measurements. The results in the literature have focuse...
Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Wills...
TSP
2010
15 years 20 days ago
Decentralized sparse signal recovery for compressive sleeping wireless sensor networks
Abstract--This paper develops an optimal decentralized algorithm for sparse signal recovery and demonstrates its application in monitoring localized phenomena using energy-constrai...
Qing Ling, Zhi Tian
INTERSPEECH
2010
15 years 24 days 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
ICASSP
2011
IEEE
14 years 9 months ago
Improved model-based spectral compressive sensing via nested least squares
This paper introduces a new algorithm for reconstructing signals with sparse spectrums from noisy compressive measurements. The proposed model-based algorithm takes the signal str...
Mahdi Shaghaghi, Sergiy A. Vorobyov