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» Biomedical signal compression based on basis pursuit
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178
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ICASSP
2011
IEEE
14 years 4 months ago
Cosparse analysis modeling - uniqueness and algorithms
In the past decade there has been a great interest in a synthesis-based model for signals, based on sparse and redundant representations. Such a model assumes that the signal of i...
Sangnam Nam, Michael E. Davies, Michael Elad, R&ea...
83
Voted
CORR
2010
Springer
95views Education» more  CORR 2010»
15 years 22 days ago
Statistical Compressive Sensing of Gaussian Mixture Models
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
Guoshen Yu, Guillermo Sapiro
ICA
2010
Springer
15 years 1 months ago
A Multichannel Spatial Compressed Sensing Approach for Direction of Arrival Estimation
Abstract. In this work, we present a direction-of-arrival (DOA) estimation method for narrowband sources impinging from the far-field on a uniform linear array (ULA) of sensors, ba...
Aris Gretsistas, Mark D. Plumbley
140
Voted
ICASSP
2011
IEEE
14 years 4 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
112
Voted
ICASSP
2010
IEEE
15 years 25 days ago
Kronecker product matrices for compressive sensing
Compressive sensing (CS) is an emerging approach for acquisition of signals having a sparse or compressible representation in some basis. While CS literature has mostly focused on...
Marco F. Duarte, Richard G. Baraniuk