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Blind Separation Based on an Evolutionary Neural Network
Barcelona, Spain September 03-September 08
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2000.90623715th International Conference on Patt ...
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Yen-Wei Chen, University of the Ryukyus
Xiang-Yan Zeng, University of the Ryukyus
Zensho Nakao, University of the Ryukyus
In this paper, we propose an evolutionary neural network for blind source separation (BSS). In the proposed method, the separating matrix is used as connection weights of the network, which are updated by a genetic algorithm (GA). A higher-order statistics of kurtosis, which is a simple and original criterion for independence, is used as a fitness function. The applicability of the proposed method for blind source separation is demonstrated by the simulation results.
Index Terms:
Blind source separation, Independent Component Analysis, genetic algorithm, Kurtosis
Citation:
Yen-Wei Chen, Xiang-Yan Zeng, Zensho Nakao, "Blind Separation Based on an Evolutionary Neural Network," icpr, vol. 2, pp.2973, 15th International Conference on Pattern Recognition (ICPR'00) - Volume 2, 2000
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