Abstract
Obtaining a low complexity activation function and an online sub-block learning for non-gaussian mixtures are presented in this paper. The paper deals with independent component analysis with mutual information as a cost function. First, we propose a low complexity activation function for non-gaussian mixtures, and then an online sub-block learning for stationary mixture is introduced. The size of the sub-blocks is larger than the maximal frequency Fmax of the principal component of the original signals. Experimental results proved that the proposed activation function and the online sub-block learning method are more efficient in terms of computational complexity as well as in terms of learning ability.
| Original language | English |
|---|---|
| Title of host publication | Knowledge-Based Intelligent Information and Engineering Systems - 7th International Conference, KES 2003, Proceedings |
| Editors | Vasile Palade, Robert J. Howlett, Lakhmi Jain |
| Place of Publication | Berlin |
| Publisher | Springer Verlag |
| Pages | 653-669 |
| Number of pages | 17 |
| Volume | 2773 |
| ISBN (Electronic) | 978-3-540-45224-9 |
| ISBN (Print) | 978-3-540-40803-1 |
| DOIs | |
| Publication status | Published - 2003 |
| Externally published | Yes |
| Event | 7th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2003 - Oxford, United Kingdom Duration: 3 Sep 2003 → 5 Sep 2003 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 2773 |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Conference
| Conference | 7th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2003 |
|---|---|
| Country | United Kingdom |
| City | Oxford |
| Period | 3/09/03 → 5/09/03 |
Keywords
- Blind signal separation
- Independent component analysis
- Mutual information
- Unsupervised neural networks
ASJC Scopus subject areas
- Computer Science(all)
- Theoretical Computer Science
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Cite this
Chinnasarn, K., Lursinsap, C., & Palade, V. (2003). Low Complexity Functions for Stationary Independent Component Mixtures. In V. Palade, R. J. Howlett, & L. Jain (Eds.), Knowledge-Based Intelligent Information and Engineering Systems - 7th International Conference, KES 2003, Proceedings (Vol. 2773, pp. 653-669). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2773). Berlin: Springer Verlag. https://doi.org/10.1007/978-3-540-45224-9_90