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Auditory-motivated Gammatone wavelet transform
Department of Electrical Engineering, Indian Institute of Science, Bangalore 560012, India.
Indian Institute of Science Bangalore. (Department of Electrical Engineering)
Indian Institute of Science Bangalore. (Department of Electrical Engineering)
2014 (English)In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 94, 608-619 p.Article in journal (Refereed) Published
Abstract [en]

The ability of the continuous wavelet transform (CWT) to provide good time and frequency localization has made it a popular tool in time-frequency analysis of signals. Wavelets exhibit constant-Q property, which is also possessed by the basilar membrane filters in the peripheral auditory system. The basilar membrane filters or auditory filters are often modeled by a Gammatone function, which provides a good approximation to experimentally determined responses. The filterbank derived from these filters is referred to as a Gammatone filterbank. In general, wavelet analysis can be likened to a filterbank analysis and hence the interesting link between standard wavelet analysis and Gammatone filterbank. However, the Gammatone function does not exactly qualify as a wavelet because its time average is not zero. We show how bona fide wavelets can be constructed out of Gammatone functions. We analyze properties such as admissibility, time-bandwidth product, vanishing moments, which are particularly relevant in the context of wavelets. We also show how the proposed auditory wavelets are produced as the impulse response of a linear, shift-invariant system governed by a linear differential equation with constant coefficients. We propose analog circuit implementations of the proposed CWT. We also show how the Gammatone-derived wavelets can be used for singularity detection and time-frequency analysis of transient signals.

Place, publisher, year, edition, pages
2014. Vol. 94, 608-619 p.
Keyword [en]
Continuous wavelet transform, Gammatone function, Auditory wavelet, Vanishing moments, Singularity detection
National Category
Signal Processing
URN: urn:nbn:se:kth:diva-131268DOI: 10.1016/j.sigpro.2013.07.029ISI: 000327363300063ScopusID: 2-s2.0-84883194522OAI: diva2:655190

QC 20140203

Available from: 2013-10-10 Created: 2013-10-10 Last updated: 2014-02-03Bibliographically approved

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Venkitarman, Arun
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