A Hierarchical Self-orginising Map Model for Sequence Recognition |
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Authors: | Carpinteiro O.A.S. |
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Affiliation: | (1) Instituto de Engenharia Elétrica, Escola Federal de Engenharia de Itajubá, Brazil, BR |
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Abstract: | This paper presents an analysis of an original hierarchical neural model on a complex sequence - the complete sixteenth fourpart fugue in G minor of the Well-Tempered Clavier (vol 1) of J. S. Bach. The model makes an effective use of context information, through its hierarchical topology and embedded time integrators, and that enables it to keep a very good account of past events. The model performs sequence classification and discrimination efficiently. It has application in domains which require pattern recognition, or particulary, which demand recognising either a set if sequences of vectors in time, or sub-sequences into a unique and large sequence of vectors in time. Received: 16 March 1999, Received in revised form: 30 July 1999, Accepted: 27 September 1999 |
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Keywords: | : Artificial intelligence Artificial neural networks Pattern recognition Self-organising map |
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