1994The Journal of the Acoustical Society of AmericaOpen access

Composite wavelet transform as an auditory model

Wade Trappe, Joseph D. Lakey

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Abstract

Motivated by the human auditory system, a new signal transform is presented which models the way humans hear. Cochlear processing acts like a constant bandwidth bank of filters in the low-frequency range but is of proportional bandwidth at higher frequencies. This new transform, which we call the composite wavelet transform, is better able to model this process than standard signal processing techniques such as the short-time fourier transform (STFT) and the continuous wavelet transform (CWT). The composite wavelet transform in fact provides a signal analysis tool that is able to examine signals with competing signal structures whereas the STFT and the CWT do not. Numerical results for this transform are presented along with a comparison to the STFT and the CWT.

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What this paper is about

Motivated by the human auditory system, a new signal transform is presented which models the way humans hear. Cochlear processing acts like a constant bandwidth bank of filters in the low-frequency range but is of proportional bandwidth at higher frequencies. This new transform, which we call the composite wavelet transform, is better able to model this process than standard signal processing techniques such as the short-time fourier transform (STFT) and the continuous wavelet transform (CWT). The composite wavelet transform in fact provides a signal analysis tool that is able to examine signals with competing signal structures whereas the STFT and the CWT do not. Numerical results for this transform are presented along with a comparison to the STFT and the CWT.

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Available abstract

Motivated by the human auditory system, a new signal transform is presented which models the way humans hear. Cochlear processing acts like a constant bandwidth bank of filters in the low-frequency range but is of proportional bandwidth at higher frequencies. This new transform, which we call the composite wavelet transform, is better able to model this process than standard signal processing techniques such as the short-time fourier transform (STFT) and the continuous wavelet transform (CWT). The composite wavelet transform in fact provides a signal analysis tool that is able to examine signals with competing signal structures whereas the STFT and the CWT do not. Numerical results for this transform are presented along with a comparison to the STFT and the CWT.

Key concepts: Short-time Fourier transform, Constant Q transform, Harmonic wavelet transform, Wavelet transform, Second-generation wavelet transform, Discrete wavelet transform, Wavelet, Continuous wavelet transform

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