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2007
Springer

An enhanced self-organizing incremental neural network for online unsupervised learning

11 years 9 months ago
An enhanced self-organizing incremental neural network for online unsupervised learning
An enhanced self-organizing incremental neural network (ESOINN) is proposed to accomplish online unsupervised learning tasks. It improves the self-organizing incremental neural network (SOINN) [Shen, F., Hasegawa, O. (2006a). An incremental network for on-line unsupervised classification and topology learning. Neural Networks, 19, 90–106] in the following respects: (1) it adopts a single-layer network to take the place of the two-layer network structure of SOINN; (2) it separates clusters with high-density overlap; (3) it uses fewer parameters than SOINN; and (4) it is more stable than SOINN. The experiments for both the artificial dataset and the real-world dataset also show that ESOINN works better than SOINN. c 2007 Elsevier Ltd. All rights reserved.
Shen Furao, Tomotaka Ogura, Osamu Hasegawa
Added 27 Dec 2010
Updated 27 Dec 2010
Type Journal
Year 2007
Where NN
Authors Shen Furao, Tomotaka Ogura, Osamu Hasegawa
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