Multiple Matrix Rank Minimization Approach to Audio Declipping

Ryohei SASAKI  Katsumi KONISHI  Tomohiro TAKAHASHI  Toshihiro FURUKAWA  

IEICE TRANSACTIONS on Information and Systems   Vol.E101-D   No.3   pp.821-825
Publication Date: 2018/03/01
Publicized: 2017/12/06
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2017EDL8129
Type of Manuscript: LETTER
Category: Speech and Hearing
audio declipping,  signal resortoration,  switched AR model,  sparse optimization,  compressed sensing,  

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This letter deals with an audio declipping problem and proposes a multiple matrix rank minimization approach. We assume that short-time audio signals satisfy the autoregressive (AR) model and formulate the declipping problem as a multiple matrix rank minimization problem. To solve this problem, an iterative algorithm is provided based on the iterative partial matrix shrinkage (IPMS) algorithm. Numerical examples show its efficiency.