@article{Ramos_Oscar_Alberto_Magnitude_2014,
author={Ramos, Oscar Alberto and Tommasini, Fabián Carlos},
howpublished={online},
year={2014},
abstract={Principal components analysis (PCA) is frequently used for modelling the
magnitude of the head-related transfer functions (HRTFs). Assuming that
the HRTFs are minimum phase systems, the phase is obtained from the
Hilbert transform of the log-magnitude. In recent years, the PCA applied
to HRTFs is also used to model individual HRTFs relating the PCA weights
with anthropometric measurements of the head, torso and pinnae. The HRTF
log-magnitude is the most used format of input data to the PCA, but it has
been shown that if the input data is HRTF linear magnitude, the cumulative
variance converges faster, and the mean square error (MSE) is smaller.
This study demonstrates that PCA applied directly on HRTF complex values
is even better than the two formats mentioned above, that is, the MSE is
the smallest and the cumulative variance converges faster after the 8th
principal component. Different objective experiments around all the median
plane put in evidence the differences which, although small, seem to be
perceptually detectable. To elucidate this point, psychoacoustic
discrimination tests are done between measured and reconstructed HRTFs
from the three types of input data mentioned, in the median plane between
-45°. and +9°.},
type={Artykuły / Articles},
title={Magnitude Modelling of HRTF Using Principal Component Analysis Applied to Complex Values},
volume={vol. 39},
number={No 4},
pages={477-482},
journal={Archives of Acoustics},
publisher={Committee on Acoustics PAS, PAS Institute of Fundamental Technological Research, Polish Acoustical Society},
doi={10.2478/aoa-2014-0051},
keywords={HRTF, PCA, binaural audition, auditory perception},
}