Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
562563 | Signal Processing | 2014 | 8 Pages |
Abstract
This paper proposes a new matrix shrinkage algorithm for matrix rank minimization problems. The proposed algorithm provides a low rank solution by estimating a matrix rank and shrinking non-dominant singular values iteratively. We study the convergence properties of the algorithm, which indicate that the algorithm gives approximate low-rank solutions. Numerical results show that the proposed algorithm works efficiently for hard problems with low computing time.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Katsumi Konishi, Kazunori Uruma, Tomohiro Takahashi, Toshihiro Furukawa,