Block Adaptive Algorithm for Signal Declipping Based on Null Space Alternating Optimization

Author:

TAKAHASHI Tomohiro1,URUMA Kazunori1,KONISHI Katsumi2,FURUKAWA Toshihiro1

Affiliation:

1. Department of Management Science, Tokyo University of Science

2. Department of Computer Science, Kogakuin University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Reference10 articles.

1. [1] J. Tang, “Evaluation of double sided periodic substitution (DSPS) method for recovering missing speech in packet voice communications,” Proc. Tenth Annual International Phoenix Conference on Computers and Communications, pp.454-458, 1991.

2. [2] A. Janssen, R. Veldhuis, and L. Vries, “Adaptive interpolation of discrete-time signals that can be modeled as autoregressive processes,” IEEE Trans. Acoust. Speech Signal Process., vol.34, no.2, pp.317-330, 1986.

3. [3] S.J. Godsill, P.J. Wolfe, and W.N.W. Fong, “Statistical model-based approaches to audio restoration and analysis,” J. New Music Research, vol.30, no.4, pp.323-338, 2001.

4. [4] A. Adler, V. Emiya, M. Jafori, M. Elad, R. Gribonval, and M.D. Plimbley, “A constrained matching pursuit approach to audio declipping,” Proc. IEEE ICASSP, pp.329-332, 2011.

5. [5] T. Takahashi, K. Konishi, and T. Furukawa, “Hankel structured matrix rank minimization approach to signal declipping,” Proc. EUSIPCO, pp.1-5, 2013.

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2. Audio declipping performance enhancement via crossfading;Signal Processing;2022-03

3. A Survey and an Extensive Evaluation of Popular Audio Declipping Methods;IEEE Journal of Selected Topics in Signal Processing;2021-01

4. Multiple Matrix Rank Minimization Approach to Audio Declipping;IEICE Transactions on Information and Systems;2018

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