From otoacoustic emission modeling to bionic wavelet transform

J. Yao; Y. T. Zhang

doi:10.1109/iembs.2000.900736

From otoacoustic emission modeling to bionic wavelet transform

J. Yao, Y. T. Zhang

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

8 Citations (Scopus)

Abstract

Bionic Wavelet Transform (BWT), a new real-time adaptive method, is proposed in this paper based on the understanding of periphery hearing system. The resolutions of BWT in the time-frequency domain can be adaptively adjusted not only by the signal frequency but also by other parameters of the signal, such as signal amplitude. Simulation result shows new properties in time-frequency representation of this nonlinear transform.

Original language	English
Pages (from-to)	314-316
Journal	Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Proceedings
Volume	1
DOIs	https://doi.org/10.1109/iembs.2000.900736
Publication status	Published - 2000
Externally published	Yes
Event	22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Chicago, IL, United States Duration: 23 Jul 2000 → 28 Jul 2000

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

Bionic wavelet transform
Otoacoustic emission

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title = "From otoacoustic emission modeling to bionic wavelet transform",

abstract = "Bionic Wavelet Transform (BWT), a new real-time adaptive method, is proposed in this paper based on the understanding of periphery hearing system. The resolutions of BWT in the time-frequency domain can be adaptively adjusted not only by the signal frequency but also by other parameters of the signal, such as signal amplitude. Simulation result shows new properties in time-frequency representation of this nonlinear transform.",

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AU - Yao, J.

AU - Zhang, Y. T.

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

PY - 2000

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N2 - Bionic Wavelet Transform (BWT), a new real-time adaptive method, is proposed in this paper based on the understanding of periphery hearing system. The resolutions of BWT in the time-frequency domain can be adaptively adjusted not only by the signal frequency but also by other parameters of the signal, such as signal amplitude. Simulation result shows new properties in time-frequency representation of this nonlinear transform.

AB - Bionic Wavelet Transform (BWT), a new real-time adaptive method, is proposed in this paper based on the understanding of periphery hearing system. The resolutions of BWT in the time-frequency domain can be adaptively adjusted not only by the signal frequency but also by other parameters of the signal, such as signal amplitude. Simulation result shows new properties in time-frequency representation of this nonlinear transform.

KW - Bionic wavelet transform

KW - Otoacoustic emission

UR - http://www.scopus.com/inward/record.url?scp=0034440765&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0034440765&origin=recordpage

U2 - 10.1109/iembs.2000.900736

DO - 10.1109/iembs.2000.900736

M3 - RGC 21 - Publication in refereed journal

SN - 0589-1019

VL - 1

SP - 314

EP - 316

JO - Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Proceedings

JF - Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Proceedings

T2 - 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Y2 - 23 July 2000 through 28 July 2000

ER -

From otoacoustic emission modeling to bionic wavelet transform

Abstract

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Research Keywords

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