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

Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/43213

DC Field	Value
dc.title	ART-C: A neural architecture for self-organization under constraints
dc.contributor.author	He, J.
dc.contributor.author	Tan, A.-H.
dc.contributor.author	Tan, C.-L.
dc.date.accessioned	2013-07-23T09:28:03Z
dc.date.available	2013-07-23T09:28:03Z
dc.date.issued	2002
dc.identifier.citation	He, J.,Tan, A.-H.,Tan, C.-L. (2002). ART-C: A neural architecture for self-organization under constraints. Proceedings of the International Joint Conference on Neural Networks 3 : 2550-2555. ScholarBank@NUS Repository.
dc.identifier.uri	http://scholarbank.nus.edu.sg/handle/10635/43213
dc.description.abstract	This paper proposes a novel 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.
dc.source	Scopus
dc.subject	Adaptive resonance theory
dc.subject	Constraint clustering
dc.subject	Machine learning
dc.type	Conference Paper
dc.contributor.department	COMPUTER SCIENCE
dc.contributor.department	INSTITUTE OF SYSTEMS SCIENCE
dc.description.sourcetitle	Proceedings of the International Joint Conference on Neural Networks
dc.description.volume	3
dc.description.page	2550-2555
dc.description.coden	85OFA
dc.identifier.isiut	NOT_IN_WOS
Appears in Collections:	Staff Publications

There are no files associated with this item.

Check