Shrinkage tuning based on an unbiased MSE estimate for sparsity-aware adaptive filtering

Masao Yamagishi, Masahiro Yukawa, Isao Yamada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Effective utilization of sparsity of the system to be estimated is a key to achieve excellent adaptive filtering performances. This can be realized by the adaptive proximal forward-backward splitting (APFBS) with carefully chosen parameters. In this paper, we propose a systematic parameter tuning based on a minimization principle of an unbiased MSE estimate. Thanks to the piecewise quadratic structure of the proposed MSE estimate, we can obtain its minimizer with low computational load. A numerical example demonstrates the efficacy of the proposed parameter tuning by its excellent performance over a broader range of SNR than a heuristic parameter tuning of the APFBS.

Original languageEnglish
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5477-5481
Number of pages5
ISBN (Print)9781479928927
DOIs
Publication statusPublished - 2014
Event2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italy
Duration: 2014 May 42014 May 9

Other

Other2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
CountryItaly
CityFlorence
Period14/5/414/5/9

Fingerprint

Adaptive filtering
Tuning

Keywords

  • Mallow's Cp statistic
  • proximity operator
  • Shrinkage parameter tuning
  • sparsity-aware adaptive filtering
  • Stein's lemma

ASJC Scopus subject areas

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

Cite this

Yamagishi, M., Yukawa, M., & Yamada, I. (2014). Shrinkage tuning based on an unbiased MSE estimate for sparsity-aware adaptive filtering. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (pp. 5477-5481). [6854650] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2014.6854650

Shrinkage tuning based on an unbiased MSE estimate for sparsity-aware adaptive filtering. / Yamagishi, Masao; Yukawa, Masahiro; Yamada, Isao.

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. p. 5477-5481 6854650.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yamagishi, M, Yukawa, M & Yamada, I 2014, Shrinkage tuning based on an unbiased MSE estimate for sparsity-aware adaptive filtering. in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings., 6854650, Institute of Electrical and Electronics Engineers Inc., pp. 5477-5481, 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014, Florence, Italy, 14/5/4. https://doi.org/10.1109/ICASSP.2014.6854650
Yamagishi M, Yukawa M, Yamada I. Shrinkage tuning based on an unbiased MSE estimate for sparsity-aware adaptive filtering. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2014. p. 5477-5481. 6854650 https://doi.org/10.1109/ICASSP.2014.6854650
Yamagishi, Masao ; Yukawa, Masahiro ; Yamada, Isao. / Shrinkage tuning based on an unbiased MSE estimate for sparsity-aware adaptive filtering. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 5477-5481
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