Basis pursuit denoising

Known as: BPDN 
In applied mathematics and statistics, basis pursuit denoising (BPDN) refers to a mathematical optimization problem of the form: where is a parameter… (More)
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2016
2016
When Lamb waves propagates in composite laminates, the direction-dependent property parameters of the composite laminates lead to… (More)
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2013
2013
The number of available algorithms for the so-called Basis Pursuit Denoising problem (or the related LASSO-problem) is large and… (More)
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2011
2011
We introduce a fast method, the “in-crowd” algorithm, for finding the exact solution to basis pursuit denoising problems. The in… (More)
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Highly Cited
2011
Highly Cited
2011
We consider the problem of decomposing a signal into a linear combination of features, each a continuously translated version of… (More)
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2010
2010
For compressive sensing (CS), we explore the framework of Bayesian linear models to achieve a robust reconstruction performance… (More)
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Highly Cited
2010
Highly Cited
2010
In this work, we study the problem of reconstructing a sparse signal from a limited number of linear ‘incoherent’ noisy… (More)
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2009
2009
  • A. Rakotomamonjy LITIS
  • 2009
We address the problem of learning a joint sparse approximation of several signals over a dictionary. We posethe problem as a… (More)
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Highly Cited
2008
Highly Cited
2008
The basis pursuit problem seeks a minimum one-norm solution of an underdetermined least-squares problem. Basis pursuit denoise… (More)
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Highly Cited
2006
Highly Cited
2006
A simultaneous sparse approximation problem requests a good approximation of several input signals at once using different linear… (More)
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Highly Cited
2000
Highly Cited
2000
The so-called denoising problem, relative to normal models for noise, is formalized such that`noise' is deened as the… (More)
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