Self-Organizing neural networks for signal recognition

Authors:
Jan Koutník;Miroslav Šnorek
Affiliations:
Department of Computer Science and Engineering, Czech Technical University, Prague, Czech Republic;Department of Computer Science and Engineering, Czech Technical University, Prague, Czech Republic
Venue:
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Year:
2006

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Abstract

In this paper we introduce a self-organizing neural network that is capable of recognition of temporal signals. Conventional self-organizing neural networks like recurrent variant of Self-Organizing Map provide clustering of input sequences in space and time but the identification of the sequence itself requires supervised recognition process, when such network is used. In our network called TICALM the recognition is expressed by speed of convergence of the network while processing either learned or an unknown signal. TICALM network capabilities are shown on an experiment with handwriting recognition.