DocumentCode
1575484
Title
On a novel adaptive self organizing network
Author
Kawahara, Shingo ; Saito, Toshimichi
Author_Institution
Dept. of Electr. Eng., Hosei Univ., Tokyo, Japan
fYear
1996
Firstpage
41
Lastpage
46
Abstract
In this paper a new algorithm is presented in order to overcome the stability vs. formation ability dilemma of competitive learning. This algorithm is based on growing cell structures of self-organizing mapping. The new algorithm is effective for endless learning and automatic classification. Applying the algorithm in the case where the input pattern is changed temporally, we have confirmed that it has much better performance than conventional algorithms
Keywords
cellular neural nets; pattern classification; self-organising feature maps; unsupervised learning; adaptive self organizing network; automatic classification; competitive learning; endless learning; formation ability; growing cell structures; input pattern; self-organizing mapping; stability; Adaptive systems; Automatic control; Cellular neural networks; Classification algorithms; Counting circuits; Frequency; Iron; Probability distribution; Self-organizing networks; Stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Neural Networks and their Applications, 1996. CNNA-96. Proceedings., 1996 Fourth IEEE International Workshop on
Conference_Location
Seville
Print_ISBN
0-7803-3261-X
Type
conf
DOI
10.1109/CNNA.1996.566487
Filename
566487
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