Preprint of the project: miscellaneous activities
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.
