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Iterative Cosparse Projection Algorithms for the Recovery of Cosparse Vectors

Abstract : Recently, a cosparse analysis model was introduced as an alternative to the standard sparse synthesis model. This model was shown to yield uniqueness guarantees in the context of linear inverse problems, and a new reconstruction algorithm was provided, showing improved performance compared to analysis $\ell_1$ optimization. In this work we pursue the parallel between the two models and propose a new family of algorithms mimicking the family of Iterative Hard Thresholding algorithms, but for the cosparse analysis model. We provide performance guarantees for algorithms from this family under a Restricted Isometry Property adapted to the context of analysis models, and we demonstrate the performance of the algorithms on simulations.
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Submitted on : Tuesday, July 26, 2011 - 4:01:42 PM
Last modification on : Friday, February 4, 2022 - 3:09:13 AM
Long-term archiving on: : Monday, November 7, 2011 - 11:32:39 AM


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  • HAL Id : inria-00611592, version 1


Raja Giryes, Sangnam Nam, Rémi Gribonval, Mike E. Davies. Iterative Cosparse Projection Algorithms for the Recovery of Cosparse Vectors. The 19th European Signal Processing Conference (EUSIPCO‐2011), 2011, Barcelona, Spain. ⟨inria-00611592⟩



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