Rate of Convergence of the FOCUSS Algorithm.
basic_science · Level V
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- Record sourced from PubMed, PMID 26955054.
- Also identified by DOI 10.1109/TNNLS.2016.2532358.
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Abstract
Focal underdetermined system solver (FOCUSS) is a powerful method for basis selection and sparse representation, where it employs the [Formula: see text]-norm with p ∈ (0,2) to measure the sparsity of solutions. In this paper, we give a systematical analysis on the rate of convergence of the FOCUSS algorithm with respect to p ∈ (0,2) . We prove that the FOCUSS algorithm converges superlinearly for and linearly for usually, but may superlinearly in some very special scenarios. In addition, we verify its rates of convergence with respect to p by numerical experiments.