Adaptive Filtering for Non-Gaussian Processes

Preben Kidmose

doi:10.1109/ICASSP.2000.861999

Adaptive Filtering for Non-Gaussian Processes

Preben Kidmose

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Abstract

A new stochastic gradient robust filtering method, based on a non-linear amplitude transformation, is proposed. The method requires no a priori knowledge of the characteristics of the input signals and it is insensitive to the signals distribution and to the stationarity of the signals. A simulation study, applying both synthetic and real-world signals, shows that the proposed method has overall better robustness performance, in terms of modeling error, compared with state-of-the-art robust filtering methods. A remarkable property of the proposed method is that it can handle double-talk in the acoustical echo-cancellation problem.

Original language	English
Title of host publication	Proceedings of International Conference on Acoustics, Speech and Signal Processing, ICASSP2000
Publisher	IEEE
Publication date	2000
Pages	424-427
ISBN (Print)	0-7803-6293-4
DOIs	https://doi.org/10.1109/ICASSP.2000.861999
Publication status	Published - 2000
Event	Proceedings of International Conference on Acoustics, Speech and Signal Processing, ICASSP2000 - Duration: 1 Jan 2000 → …

Conference

Conference	Proceedings of International Conference on Acoustics, Speech and Signal Processing, ICASSP2000
Period	01/01/2000 → …

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Copyright 2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

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title = "Adaptive Filtering for Non-Gaussian Processes",

abstract = "A new stochastic gradient robust filtering method, based on a non-linear amplitude transformation, is proposed. The method requires no a priori knowledge of the characteristics of the input signals and it is insensitive to the signals distribution and to the stationarity of the signals. A simulation study, applying both synthetic and real-world signals, shows that the proposed method has overall better robustness performance, in terms of modeling error, compared with state-of-the-art robust filtering methods. A remarkable property of the proposed method is that it can handle double-talk in the acoustical echo-cancellation problem.",

author = "Preben Kidmose",

note = "Copyright 2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.; Proceedings of International Conference on Acoustics, Speech and Signal Processing, ICASSP2000 ; Conference date: 01-01-2000",

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doi = "10.1109/ICASSP.2000.861999",

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N1 - Copyright 2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2000

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N2 - A new stochastic gradient robust filtering method, based on a non-linear amplitude transformation, is proposed. The method requires no a priori knowledge of the characteristics of the input signals and it is insensitive to the signals distribution and to the stationarity of the signals. A simulation study, applying both synthetic and real-world signals, shows that the proposed method has overall better robustness performance, in terms of modeling error, compared with state-of-the-art robust filtering methods. A remarkable property of the proposed method is that it can handle double-talk in the acoustical echo-cancellation problem.

AB - A new stochastic gradient robust filtering method, based on a non-linear amplitude transformation, is proposed. The method requires no a priori knowledge of the characteristics of the input signals and it is insensitive to the signals distribution and to the stationarity of the signals. A simulation study, applying both synthetic and real-world signals, shows that the proposed method has overall better robustness performance, in terms of modeling error, compared with state-of-the-art robust filtering methods. A remarkable property of the proposed method is that it can handle double-talk in the acoustical echo-cancellation problem.

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DO - 10.1109/ICASSP.2000.861999

M3 - Article in proceedings

SN - 0-7803-6293-4

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EP - 427

BT - Proceedings of International Conference on Acoustics, Speech and Signal Processing, ICASSP2000

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T2 - Proceedings of International Conference on Acoustics, Speech and Signal Processing, ICASSP2000

Y2 - 1 January 2000

ER -

Adaptive Filtering for Non-Gaussian Processes

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