2 research outputs found

    Stability analysis of an unsupervised competitive neural network

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    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

    Stability Analysis of an Unsupervised Competitive Neural Network

    No full text
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