A Hierarchical Self-Organizing Map Model for Sequence Recognition

Authors:
Otávio Augusto S. Carpinteiro
Affiliations:
Instituto de Engenharia Elétrica, Escola Federal de Engenharia de Itajubá, Av. BPS 1303, Itajubá, MG, 37500–000, Brazil, e-mail: otavio@iee.efei.br
Venue:
Neural Processing Letters
Year:
1999

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Abstract

A novel neural model made up of two self-organizing maps nets – one on top of the other – is introduced and analysed experimentally. The model makes effective use of context information, and that enables it to perform sequence classification and discrimination efficiently. It was successfully applied to real sequences, taken from the third voice of the sixteenth four-part fugue in G minor of the Well-Tempered Clavier (vol. I) of J.S. Bach. The model has an application in domains which require pattern recognition, or more specifically, which demand the recognition of either a set of sequences of vectors in time or sub-sequences into a unique and large sequence of vectors in time.