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» Support Recovery of Sparse Signals
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ICASSP
2011
IEEE
14 years 1 months ago
Focuss is a convex-concave procedure
We show the powerful sparse signal recovery approach FOCUSS is a convex-concave procedure. It follows a Newton-like decent direction by retaining the positive definite component ...
Mashud Hyder, Kaushik Mahata
CORR
2008
Springer
194views Education» more  CORR 2008»
14 years 9 months ago
Combining geometry and combinatorics: A unified approach to sparse signal recovery
Radu Berinde, Anna C. Gilbert, Piotr Indyk, Howard...
ICASSP
2011
IEEE
14 years 1 months ago
Bayesian Compressive Sensing for clustered sparse signals
In traditional framework of Compressive Sensing (CS), only sparse prior on the property of signals in time or frequency domain is adopted to guarantee the exact inverse recovery. ...
Lei Yu, Hong Sun, Jean-Pierre Barbot, Gang Zheng
ICASSP
2008
IEEE
15 years 3 months ago
Average case analysis of sparse recovery with thresholding : New bounds based on average dictionary coherence
This paper analyzes the performance of the simple thresholding algorithm for sparse signal representations. In particular, in order to be more realistic we introduce a new probabi...
Mohammad Golbabaee, Pierre Vandergheynst
ICASSP
2011
IEEE
14 years 1 months ago
Sparse spectral factorization: Unicity and reconstruction algorithms
Spectral factorization is a classical tool in signal processing and communications. It also plays a critical role in X-ray crystallography, in the context of phase retrieval. In t...
Yue M. Lu, Martin Vetterli