An Efficient Algorithm for Sparse Representations with ` p Data Fidelity Term

@inproceedings{Rodrguez2008AnEA,
  title={An Efficient Algorithm for Sparse Representations with ` p Data Fidelity Term},
  author={Paul Rodrı́guez and Brendt Wohlberg},
  year={2008}
}
Basis Pursuit (BP) and Basis Pursuit Denoising (BPDN), well established techniques for computing sparse representations, minimize an ` data fidelity term, subject to an ` sparsity constraint or regularization term, by mapping the problem to a linear or quadratic program. BPDN with an ` data fidelity term has recently been proposed, also implemented via a mapping to a linear program. We introduce an alternative approach via an Iteratively Reweighted Least Squares algorithm, providing… CONTINUE READING

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