Abstract
In this paper, we propose to employ an extension to the natural gradient algorithm for robust Independent Component Analysis against outliers. The standard natural gradient algorithm does not exhibit this property since it employs nonrobust sample estimates for computing higher order moments. In order to overcome this drawback, we propose to use robust alternatives to higher order moments, which are comparatively less sensitive to outliers in the observed data. Some computer simulations are presented to show that the proposed method, as compared to the standard natural gradient algorithm, gives better performance in the presence of outlying data.
| Original language | English |
|---|---|
| Pages (from-to) | 2429-2432 |
| Number of pages | 4 |
| Journal | IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences |
| Volume | E89-A |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - 2006 Sept |
| Externally published | Yes |
Keywords
- Independent Component Analysis
- Outliers
- Robust higher order statistics
ASJC Scopus subject areas
- Signal Processing
- Computer Graphics and Computer-Aided Design
- Electrical and Electronic Engineering
- Applied Mathematics