350 rub
Journal Neurocomputers №2 for 2014 г.
Article in number:
Neural network methods for the problems of cluster analysis
Keywords: cluster analysis model Kuramoto self-organized map chaotic neural networks oscillatory neural networks
Authors:
A.V. Novikov - Post-graduate Student, St.-Petersburg State Polytechnical University. E-mail: spb.andr@yandex.ru
E.N. Benderskaya - Ph.D. (Eng.), Professor, St.-Petersburg State Polytechnical University. E-mail: helen.bend@gmail.com
Abstract:
The article presents results of research of neural networks methods for solving problems of cluster analysis. Described general problems of input data pre-processing and output data post-processing. The content of article is divided into three main parts. In first part present presented study results as well as features and restrictions of usage oscillatory neural networks based on Kuramoto model with dynamic and static structures. The second and third parts contain study results of self-organized maps and chaotic neural networks accordingly. In conclusion summarized the major features and proposed practical recommendation for usage neural networks for cluster analysis.
Pages: 48-53
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