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Comparison of Principal Components Analysis on Linear and Logarithmic Magnitude of Head-Related Transfer Functions

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3 Author(s)
Zhiqiang Liang ; Phys. Dept., South China Univ. of Technol., Guangzhou, China ; Bosun Xie ; Xiaoli Zhong

Principal components analysis (PCA) is widely used in compression of head-related transfer function (HRTF) database. In practice, PCA is often performed on linear or logarithmic magnitude of HRTFs. These two PCA models (Linear-PCA model and Log-PCA model) were compared in this paper. Cumulative Variance Percentage, Signal-to-Distortion Ratio and Spectral Distortion were used as criterions in comparison. Results show that Cumulative Variance Percentage is inadequate to evaluate the two models, while Signal-to-Distortion Ratio and Spectral Distortion may lead to contrary conclusions. Finally, monaural loudness spectra were calculated and the results show that the Linear-PCA model is superior at most of sound source positions.

Published in:

Image and Signal Processing, 2009. CISP '09. 2nd International Congress on

Date of Conference:

17-19 Oct. 2009

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