Guarantees of Fast Band Restricted Thresholding Algorithm for Low-Rank Matrix Recovery Problem

Fujun Zhao, Jigen Peng, Kai Sun and Angang Cui

Mathematical Problems in Engineering, 2020, vol. 2020, 1-14

Abstract:

Affine matrix rank minimization problem is a famous problem with a wide range of application backgrounds. This problem is a combinatorial problem and deemed to be NP-hard. In this paper, we propose a family of fast band restricted thresholding (FBRT) algorithms for low rank matrix recovery from a small number of linear measurements. Characterized via restricted isometry constant, we elaborate the theoretical guarantees in both noise-free and noisy cases. Two thresholding operators are discussed and numerical demonstrations show that FBRT algorithms have better performances than some state-of-the-art methods. Particularly, the running time of FBRT algorithms is much faster than the commonly singular value thresholding algorithms.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:9578168

DOI: 10.1155/2020/9578168

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