A parameter-free Cauchy-Schwartz information measure for independent component analysis
Lei Sun, Badong Chen, Kar-Ann Toh, Zhiping Lin
Abstract
Independent component analysis (ICA) by an information measure has seen wide applications in engineering. Different from traditional probability density function based information measures, a probability survival distribution based Cauchy-Schwartz information measure for multiple variables is proposed in this paper. Empirical estimation of survival distribution is parameter-free which is inherited by the estimation of the new information measure. This measure is proved to be a valid statistical independence measure and is adopted as an objective function to develop an ICA algorithm which is validated by an experiment. This work shows promising potential regarding the use of survival distribution based information measure for ICA.
BibTeX
@inproceedings{icassp2016_aparameterfreeca,
title = {A parameter-free Cauchy-Schwartz information measure for independent component analysis},
author = {Lei Sun and Badong Chen and Kar-Ann Toh and Zhiping Lin},
booktitle = {ICASSP 2016},
year = {2016}
}