Meyer-Bäse, A. and Thümmler, V. and Theis, Fabian J. (2006) Stability analysis of an unsupervised competitive neural network. In: International Joint Conference on Neural Networks, IJCNN '06 : 16 - 21 July 2006, Vancouver, BC, Canada, 16 - 21 July 2006; proceedings. IEEE Service Center, Piscataway, NJ. ISBN 0-7803-9490-9.
Full text not available from this repository.
Unsupervised competitive neural networks (UCNN) are an established technique in pattern recognition for feature extraction and cluster analysis. A novel model of an unsupervised competitive neural network implementing a multi-time scale dynamics is proposed in this paper. The global asymptotic stability of the equilibrium points of this continuous-time recurrent system whose weights are adapted based on a competitive learning law is mathematically analyzed. The proposed neural network and the derived results are compared with those obtained from other multi-time scale architectures.
|Item Type:||Book Section|
|Institutions:||Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang|
|Subjects:||500 Science > 570 Life sciences|
|Created at the University of Regensburg:||Unknown|
|Deposited On:||01 Oct 2010 09:49|
|Last Modified:||01 Oct 2010 09:49|
- ASCII Citation
- Dublin Core
- HTML Citation
- OAI-ORE Resource Map (Atom Format)
- OAI-ORE Resource Map (RDF Format)
- Reference Manager
- Simple Metadata
Literature of the same author