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Adaptive algorithms for active sound-profiling

Adaptive algorithms for active sound-profiling
Adaptive algorithms for active sound-profiling
Three novel adaptive algorithms are proposed for use in active sound-profiling, all based on the filtered-X least mean square (FXLMS) approach. The algorithms are analyzed for their stability properties and control effort load, and are compared with the currently used adaptive noise equalizer least mean square (ANE-LMS) algorithm. It is found that the most suitable algorithm, both in simulations and experimentally, is the phase scheduled command FXLMS (PSC-FXLMS), which possesses both low control effort and good stability in the face of plant model misestimation, especially when using an automatic phase command law.
1558-7916
711-719
Rees, L.E.
64b90544-a94c-4c10-98b3-246dd9362fed
Elliott, S.J.
721dc55c-8c3e-4895-b9c4-82f62abd3567
Rees, L.E.
64b90544-a94c-4c10-98b3-246dd9362fed
Elliott, S.J.
721dc55c-8c3e-4895-b9c4-82f62abd3567

Rees, L.E. and Elliott, S.J. (2006) Adaptive algorithms for active sound-profiling. IEEE Transactions on Audio, Speech and Language Processing, 14 (2), 711-719. (doi:10.1109/TSA.2005.855828).

Record type: Article

Abstract

Three novel adaptive algorithms are proposed for use in active sound-profiling, all based on the filtered-X least mean square (FXLMS) approach. The algorithms are analyzed for their stability properties and control effort load, and are compared with the currently used adaptive noise equalizer least mean square (ANE-LMS) algorithm. It is found that the most suitable algorithm, both in simulations and experimentally, is the phase scheduled command FXLMS (PSC-FXLMS), which possesses both low control effort and good stability in the face of plant model misestimation, especially when using an automatic phase command law.

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Published date: 2006

Identifiers

Local EPrints ID: 28565
URI: https://eprints.soton.ac.uk/id/eprint/28565
ISSN: 1558-7916
PURE UUID: 7dfd7495-662a-448c-ac2c-f69018f4bfe6

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Date deposited: 28 Apr 2006
Last modified: 17 Jul 2017 16:00

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