An incremental neural network for non-stationary unsupervised learning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3316, Issue , 2004, Pages 641-646

  Furao, Shen ^a   Hasegawa, Osamu ^a,b  

^a Tokyo Institute of Technology ^*  (Japan)

^b JAPAN SCIENCE AND TECHNOLOGY AGENCY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTERS;

INCREMENTAL NEURAL NETWORKS; NONSTATIONARY; NONSTATIONARY DATA; NUMBER OF CLUSTERS; ONLINE LEARNING; PROTOTYPE PATTERNS; TOPOLOGICAL STRUCTURE; UNSUPERVISED CLASSIFICATION;

TOPOLOGY;

EID: 33846971853     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-30499-9_98     Document Type: Article

References (9)

1. Likas, A., Vlassis, N., & Verbeek, J.J. (2003). "The global k-means clustering algorithm," Pattern Recognition, Vol. 36, 451-461.
2. Patane, G., & Russo, M. (2001). "The enhanced LBG algorithm," Neural Networks, Vol.14, 1219-1237.
3. Kohonen, T. (1982). "Self-organized formation of topologically correct feature maps," Biological Cybernetics, Vol 43, 59-69.
4. Martinetz, T.M., Berkovich, S.G., & Schulten, K.J. (1993). ""Neural-gas" network for vector quantization and its application to time-series prediction," IEEE Transactions on Neural Networks, Vol. 4, No. 4, 558-569.
5. Fritzke, B. (1995). "A growing neural gas network learns topologies," In Advances in neural information processing systems, 625-632.
6. Fritzke, B. (1997). "A self-organizing network that can follow non-stationary distributions," In Proceedings of ICANN-97, 613-618.
7. Hamker, F.H. (2001). "Life-long learning cell structures - continuously learning without catastrophic interference," Neural Networks, Vol. 14, 551-573.
8. Duda, R.O., Hart, P.E., & Stork, D.G. (2001). "Pattern classification, 2nd ed.," A Wiley-Interscience Publication.
9. Fritzke, B. (1994). "Growing cell structures - a self-organizing network for unsupervised and supervised learning," Neural Networks, Vol. 7, 1441-1460.