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dc.contributor.authorCarpetner, Gail A.en_US
dc.contributor.authorGrossberg, Stephenen_US
dc.contributor.authorRosen, David B.en_US
dc.date.accessioned2011-11-14T18:21:46Z
dc.date.available2011-11-14T18:21:46Z
dc.date.issued1991-02
dc.identifier.urihttps://hdl.handle.net/2144/2061
dc.description.abstractThe Fuzzy ART system introduced herein incorporates computations from fuzzy set theory into ART 1. For example, the intersection (n) operator used in ART 1 learning is replaced by the MIN operator (A) of fuzzy set theory. Fuzzy ART reduces to ART 1 in response to binary input vectors, but can also learn stable categories in response to analog input vectors. In particular, the MIN operator reduces to the intersection operator in the binary case. Learning is stable because all adaptive weights can only decrease in time. A preprocessing step, called complement coding, uses on-cell and off-cell responses to prevent category proliferation. Complement coding normalizes input vectors while preserving the amplitudes of individual feature activations.en_US
dc.description.sponsorshipAir Force Office of Scientific Research (90-0175, 90-0128); Army Research Office (DAAL-03-88-K0088); BP (89-A-1204); Defense Advanced Research Projects Agency (90-0083); National Science Foundation (IRI-90-00530)en_US
dc.language.isoen_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-1991-006
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.titleFuzzy ART: An Adaptive Resonance Algorithm for Rapid, Stable Classification of Analog Patternsen_US
dc.typeTechnical Reporten_US
dc.rights.holderBoston University Trusteesen_US


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