An Adaptive Independent Component Analysis Method

DOI

10.2991/isci-15.2015.144How to use a DOI?

Keywords

Independent Component Analysis; Blind Source Separation; Alpha Stable Distribution; General Gaussian Model

Abstract

According to the existing problem of the convention methods, an adaptive independent component analysis method is proposed. First, the signals are divided into the heavy tailed and light tailed signals according to the kurtosis. For the heavy tailed signal, the method off-line computes the score function and establishes the lookup table of the standard alpha stable distribution, and then compute the score function of the mixture signals. For the light tailed signal, the score function is estimated by the general Gaussian model. Simulated results show that, the proposed algorithm has a well performance and a lower computational complexity.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Chang Mu
AU  - Weiqin Li
PY  - 2015/01
DA  - 2015/01
TI  - An Adaptive Independent Component Analysis Method
BT  - Proceedings of the 2015 International Symposium on Computers & Informatics
PB  - Atlantis Press
SP  - 1097
EP  - 1104
SN  - 2352-538X
UR  - https://doi.org/10.2991/isci-15.2015.144
DO  - 10.2991/isci-15.2015.144
ID  - Mu2015/01
ER  -