TY - GEN
T1 - Auditory wavelet transform based on auditory wavelet families
AU - Salimpour, Y.
AU - Abolhassani, M. D.
PY - 2006/12/1
Y1 - 2006/12/1
N2 - The auditory periphery system receives a one dimensional acoustical signal that describes how the local pressure varies with time. However, this one dimensional signal information is then somehow unfolded into a two dimensional time-frequency plane, that tells us when which frequency occurs. The hearing process is based on compromise between time localization and frequency localization. A kind of time-frequency or wavelet type transformation is done in auditory signal processing. In this study the similarities between auditory transform based on the auditory physiological process and wavelet transform are introduced. Specially, band pass filter bank properties and variable time and frequency resolutions with the signal frequency are considered. The main goal is to find the scaling function while the numerical values of the wavelet function were measured. If the wavelet function and the scaling function from the measured data are estimated, then the wavelet coefficients and the scaling coefficients could be calculated. Therefore, the multiresolution implementation of auditory based wavelet transform is possible.
AB - The auditory periphery system receives a one dimensional acoustical signal that describes how the local pressure varies with time. However, this one dimensional signal information is then somehow unfolded into a two dimensional time-frequency plane, that tells us when which frequency occurs. The hearing process is based on compromise between time localization and frequency localization. A kind of time-frequency or wavelet type transformation is done in auditory signal processing. In this study the similarities between auditory transform based on the auditory physiological process and wavelet transform are introduced. Specially, band pass filter bank properties and variable time and frequency resolutions with the signal frequency are considered. The main goal is to find the scaling function while the numerical values of the wavelet function were measured. If the wavelet function and the scaling function from the measured data are estimated, then the wavelet coefficients and the scaling coefficients could be calculated. Therefore, the multiresolution implementation of auditory based wavelet transform is possible.
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U2 - 10.1109/IEMBS.2006.260717
DO - 10.1109/IEMBS.2006.260717
M3 - Conference contribution
C2 - 17946477
AN - SCOPUS:34047095431
SN - 1424400325
SN - 9781424400324
T3 - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
SP - 1731
EP - 1734
BT - 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
T2 - 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
Y2 - 30 August 2006 through 3 September 2006
ER -