New Sub-Band Adaptive Volterra Filter for Identification of Loudspeaker

Satoshi KINOSHITA; Yoshinobu KAJIKAWA

doi:10.1587/transfun.E102.A.1946

New Sub-Band Adaptive Volterra Filter for Identification of Loudspeaker

Satoshi KINOSHITA, Yoshinobu KAJIKAWA

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Adaptive Volterra filters (AVFs) are usually used to identify nonlinear systems, such as loudspeaker systems, and ordinary adaptive algorithms can be used to update the filter coefficients of AVFs. However, AVFs require huge computational complexity even if the order of the AVF is constrained to the second order. Improving calculation efficiency is therefore an important issue for the real-time implementation of AVFs. In this paper, we propose a novel sub-band AVF with high calculation efficiency for second-order AVFs. The proposed sub-band AVF consists of four parts: input signal transformation for a single sub-band AVF, tap length determination to improve calculation efficiency, switching the number of sub-bands while maintaining the estimation accuracy, and an automatic search for an appropriate number of sub-bands. The proposed sub-band AVF can improve calculation efficiency for which the dominant nonlinear components are concentrated in any frequency band, such as loudspeakers. A simulation result demonstrates that the proposed sub-band AVF can realize higher estimation accuracy than conventional efficient AVFs.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E102-A No.12 pp.1946-1955

Publication Date: 2019/12/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E102.A.1946

Type of Manuscript: PAPER

Category: Digital Signal Processing

Authors

Satoshi KINOSHITA
Kansai University
Yoshinobu KAJIKAWA
Kansai University

Keyword

sub-band adaptive Volterra filter, nonlinear system identification, loudspeaker, nonlinear distortions, multirate signal processing

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Satoshi KINOSHITA, Yoshinobu KAJIKAWA, "New Sub-Band Adaptive Volterra Filter for Identification of Loudspeaker" in IEICE TRANSACTIONS on Fundamentals, vol. E102-A, no. 12, pp. 1946-1955, December 2019, doi: 10.1587/transfun.E102.A.1946.
Abstract: Adaptive Volterra filters (AVFs) are usually used to identify nonlinear systems, such as loudspeaker systems, and ordinary adaptive algorithms can be used to update the filter coefficients of AVFs. However, AVFs require huge computational complexity even if the order of the AVF is constrained to the second order. Improving calculation efficiency is therefore an important issue for the real-time implementation of AVFs. In this paper, we propose a novel sub-band AVF with high calculation efficiency for second-order AVFs. The proposed sub-band AVF consists of four parts: input signal transformation for a single sub-band AVF, tap length determination to improve calculation efficiency, switching the number of sub-bands while maintaining the estimation accuracy, and an automatic search for an appropriate number of sub-bands. The proposed sub-band AVF can improve calculation efficiency for which the dominant nonlinear components are concentrated in any frequency band, such as loudspeakers. A simulation result demonstrates that the proposed sub-band AVF can realize higher estimation accuracy than conventional efficient AVFs.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E102.A.1946/_p

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@ARTICLE{e102-a_12_1946,
author={Satoshi KINOSHITA, Yoshinobu KAJIKAWA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={New Sub-Band Adaptive Volterra Filter for Identification of Loudspeaker},
year={2019},
volume={E102-A},
number={12},
pages={1946-1955},
abstract={Adaptive Volterra filters (AVFs) are usually used to identify nonlinear systems, such as loudspeaker systems, and ordinary adaptive algorithms can be used to update the filter coefficients of AVFs. However, AVFs require huge computational complexity even if the order of the AVF is constrained to the second order. Improving calculation efficiency is therefore an important issue for the real-time implementation of AVFs. In this paper, we propose a novel sub-band AVF with high calculation efficiency for second-order AVFs. The proposed sub-band AVF consists of four parts: input signal transformation for a single sub-band AVF, tap length determination to improve calculation efficiency, switching the number of sub-bands while maintaining the estimation accuracy, and an automatic search for an appropriate number of sub-bands. The proposed sub-band AVF can improve calculation efficiency for which the dominant nonlinear components are concentrated in any frequency band, such as loudspeakers. A simulation result demonstrates that the proposed sub-band AVF can realize higher estimation accuracy than conventional efficient AVFs.},
keywords={},
doi={10.1587/transfun.E102.A.1946},
ISSN={1745-1337},
month={December},}

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TY - JOUR
TI - New Sub-Band Adaptive Volterra Filter for Identification of Loudspeaker
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1946
EP - 1955
AU - Satoshi KINOSHITA
AU - Yoshinobu KAJIKAWA
PY - 2019
DO - 10.1587/transfun.E102.A.1946
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E102-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2019
AB - Adaptive Volterra filters (AVFs) are usually used to identify nonlinear systems, such as loudspeaker systems, and ordinary adaptive algorithms can be used to update the filter coefficients of AVFs. However, AVFs require huge computational complexity even if the order of the AVF is constrained to the second order. Improving calculation efficiency is therefore an important issue for the real-time implementation of AVFs. In this paper, we propose a novel sub-band AVF with high calculation efficiency for second-order AVFs. The proposed sub-band AVF consists of four parts: input signal transformation for a single sub-band AVF, tap length determination to improve calculation efficiency, switching the number of sub-bands while maintaining the estimation accuracy, and an automatic search for an appropriate number of sub-bands. The proposed sub-band AVF can improve calculation efficiency for which the dominant nonlinear components are concentrated in any frequency band, such as loudspeakers. A simulation result demonstrates that the proposed sub-band AVF can realize higher estimation accuracy than conventional efficient AVFs.
ER -