| Literature DB >> 17826947 |
Shen Furao1, Tomotaka Ogura, Osamu Hasegawa.
Abstract
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.Mesh:
Year: 2007 PMID: 17826947 DOI: 10.1016/j.neunet.2007.07.008
Source DB: PubMed Journal: Neural Netw ISSN: 0893-6080