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» Biomedical signal compression based on basis pursuit
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ICASSP
2011
IEEE
14 years 9 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...
CORR
2010
Springer
95views Education» more  CORR 2010»
15 years 6 months 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 7 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
ICASSP
2011
IEEE
14 years 9 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
ICASSP
2010
IEEE
15 years 6 months 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