A hierarchical self-organizing map model for sequence recognition

The paper proposes a novel neural model made up of two self-organizing map nets — one on top of the other. The model makes an effective use of context information, and that enables it to perform sequence classification and discrimination efficiently. It was trained and assessed on a four-part fugue of J. S. Bach. The model has application in domains which require pattern recognition, or in particular, which demand recognizing either a set of sequences of vectors in time or sub-sequences into a unique and large sequence of vectors in time.