@inproceedings{b8589a0fd9b842cca9338bb5d5b5eee5,
title = "Low Complexity Functions for Stationary Independent Component Mixtures",
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.",
keywords = "Blind signal separation, Independent component analysis, Mutual information, Unsupervised neural networks",
author = "K. Chinnasarn and C. Lursinsap and V. Palade",
year = "2003",
doi = "10.1007/978-3-540-45224-9_90",
language = "English",
isbn = "978-3-540-40803-1",
volume = "2773",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "653--669",
editor = "Vasile Palade and Howlett, {Robert J.} and Lakhmi Jain",
booktitle = "Knowledge-Based Intelligent Information and Engineering Systems - 7th International Conference, KES 2003, Proceedings",
address = "Austria",
note = "7th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2003 ; Conference date: 03-09-2003 Through 05-09-2003",
}