ART-C: a neural architecture for self-organization under constraints

Abstract

Proposes an ART-based neural architecture known as ART-C (ART under constraints) that performs online clustering of pattern sequences subject to the constraints on the recognition category representation. Experiments on two real-life data sets show that ART-C produces reasonably good clustering qualities, with the added advantage of high efficiency.