Stable reconstructions for the analysis formulation of ℓ^p-minimization using redundant systems

2015/09/18 by Jackie Ma, Ma, Jackie
Computer Science · Engineering · Mathematics · #FOS: Computer and information sciences #Image and Signal Denoising Methods #Information Theory (cs.IT) #Numerical methods in inverse problems #Sparse and Compressive Sensing Techniques

paper · pdf · doi:10.48550/arxiv.1509.05512

openalex publication_date 2015/09/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In compressed sensing sparse solutions are usually obtained by solving an ℓ¹-minimization problem. Furthermore, the sparsity of the signal does need not be directly given. In fact, it is sufficient to have a signal that is sparse after an application of a suitable transform. In this paper we consider the stability of solutions obtained from ℓ^p-minimization for arbitrary 0

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