An Adaptive Independent Component Analysis Method
Authors
Chang Mu, Weiqin Li
Corresponding Author
Chang Mu
Available Online January 2015.
- 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/).
Cite this article
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 -