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dc.contributor.authorCarpenter, Gail A.en_US
dc.contributor.authorGrossberg, Stephenen_US
dc.contributor.authorRosen, Daviden_US
dc.date.accessioned2011-11-14T18:21:47Z
dc.date.available2011-11-14T18:21:47Z
dc.date.issued1991-02en_US
dc.identifier.urihttp://hdl.handle.net/2144/2066
dc.description.abstractThis article introduces ART 2-A, an efficient algorithm that emulates the self-organizing pattern recognition and hypothesis testing properties of the ART 2 neural network architecture, but at a speed two to three orders of magnitude faster. Analysis and simulations show how the ART 2-A systems correspond to ART 2 dynamics at both the fast-learn limit and at intermediate learning rates. Intermediate learning rates permit fast commitment of category nodes but slow recoding, analogous to properties of word frequency effects, encoding specificity effects, and episodic memory. Better noise tolerance is hereby achieved without a loss of learning stability. The ART 2 and ART 2-A systems are contrasted with the leader algorithm. The speed of ART 2-A makes practical the use of ART 2 modules in large-scale neural computation.en_US
dc.description.sponsorshipBP (89-A-1204); Defense Advanced Research Projects Agency (90-0083); National Science Foundation (IRI-90-00530); Air Force Office of Scientific Research (90-0175, 90-0128); Army Research Office (DAAL-03-88-K0088)en_US
dc.language.isoen_USen_US
dc.publisherBoston University Center for Adaptive Systems and Department of Cognitive and Neural Systemsen_US
dc.relation.ispartofseriesBU CAS/CNS Technical Reports;CAS/CNS-TR-1991-011en_US
dc.rightsCopyright 1991 Boston University. Permission to copy without fee all or part of this material is granted provided that: 1. The copies are not made or distributed for direct commercial advantage; 2. the report title, author, document number, and release date appear, and notice is given that copying is by permission of BOSTON UNIVERSITY TRUSTEES. To copy otherwise, or to republish, requires a fee and / or special permission.en_US
dc.subjectNeural networksen_US
dc.subjectPattern recognitionen_US
dc.subjectCategory formationen_US
dc.subjectFast learningen_US
dc.subjectARTen_US
dc.titleART 2-A: An Adaptive Resonance Algorithm for Rapid Category Learning and Recognitionen_US
dc.typeTechnical Reporten_US
dc.rights.holderBoston University Trusteesen_US


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