Preprint des Projektes: Sonstiges

01/07 Anke Meyer-Bäse, Vera Thümmler.
Local and Global Stability Analysis of an Unsupervised Competitive Neural Network

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 local and 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.