Automatic shrinkage tuning based on a system-mismatch estimate for sparsity-aware adaptive filtering

Masao Yamagishi; Masahiro Yukawa; Isao Yamada

doi:10.1109/ICASSP.2017.7953068

Automatic shrinkage tuning based on a system-mismatch estimate for sparsity-aware adaptive filtering

Masao Yamagishi, Masahiro Yukawa, Isao Yamada

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

Exploiting the sparsity in learning algorithms is a key to achieve excellent performances of adaptive filters. This can be realized by the adaptive proximal forward-backward splitting with carefully chosen parameters. In this paper, we propose an automatic parameter tuning based on a minimization principle of a stochastic approximation of the system-mismatch. The proposed approximation has a Tikhonov-type regularization term, which aims to minimize the disturbance by the update of the adaptive filter and mitigates overfitting to an instantaneous observation. Thanks to these properties, the proposed method realizes adaptive parameter tuning without any user-defined parameters, unlike our previous method that utilizes the user-defined parameter to avoid over-fitting. A numerical example demonstrates the efficacy of the proposed parameter tuning.

Original language	English
Title of host publication	2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4800-4804
Number of pages	5
ISBN (Electronic)	9781509041176
DOIs	https://doi.org/10.1109/ICASSP.2017.7953068
Publication status	Published - 2017 Jun 16
Event	2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - New Orleans, United States Duration: 2017 Mar 5 → 2017 Mar 9

Other

Other	2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
Country	United States
City	New Orleans
Period	17/3/5 → 17/3/9

Keywords

adaptive proximal forward-backward splitting algorithm
automatic parameter tuning
Sparsity-aware adaptive filter

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

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10.1109/ICASSP.2017.7953068

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Yamagishi, M., Yukawa, M., & Yamada, I. (2017). Automatic shrinkage tuning based on a system-mismatch estimate for sparsity-aware adaptive filtering. In 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings (pp. 4800-4804). [7953068] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2017.7953068

Automatic shrinkage tuning based on a system-mismatch estimate for sparsity-aware adaptive filtering. / Yamagishi, Masao; Yukawa, Masahiro; Yamada, Isao.

2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 4800-4804 7953068.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yamagishi, M, Yukawa, M & Yamada, I 2017, Automatic shrinkage tuning based on a system-mismatch estimate for sparsity-aware adaptive filtering. in 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings., 7953068, Institute of Electrical and Electronics Engineers Inc., pp. 4800-4804, 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017, New Orleans, United States, 17/3/5. https://doi.org/10.1109/ICASSP.2017.7953068

Yamagishi M, Yukawa M, Yamada I. Automatic shrinkage tuning based on a system-mismatch estimate for sparsity-aware adaptive filtering. In 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 4800-4804. 7953068 https://doi.org/10.1109/ICASSP.2017.7953068

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