Minimization of the $q$-ratio sparsity with $1 < q \leq \infty$ for signal recovery

Zhiyong Zhou; Jun Yu

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arXiv · 2010.03402

Minimization of the $q$-ratio sparsity with $1 < q \leq \infty$ for signal recovery

Zhiyong Zhou·Jun Yu

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Abstract

In this paper, we propose a general scale invariant approach for sparse signal recovery via the minimization of the $q$-ratio sparsity. When $1 < q \leq \infty$, both the theoretical analysis based on $q$-ratio constrained minimal singular values (CMSV) and the practical algorithms via nonlinear fractional programming are presented. Numerical experiments are conducted to demonstrate the advantageous performance of the proposed approaches over the state-of-the-art sparse recovery methods.

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Zhiyong Zhou, Jun Yu. 2020-10-07. Minimization of the $q$-ratio sparsity with $1 < q \leq \infty$ for signal recovery. https://arxiv.org/abs/2010.03402

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