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dc.contributor.authorCarpenter, Gailen_US
dc.date.accessioned2011-11-14T19:02:09Z
dc.date.available2011-11-14T19:02:09Z
dc.date.issued2000-09en_US
dc.identifier.urihttp://hdl.handle.net/2144/2258
dc.description.abstractAdaptive resonance is a theory of cognitive information processing which has been realized as a family of neural network models. In recent years, these models have evolved to incorporate new capabilities in the cognitive, neural, computational, and technological domains. Minimal models provide a conceptual framework, for formulating questions about the nature of cognition; an architectural framework, for mapping cognitive functions to cortical regions; a semantic framework, for precisely defining terms; and a computational framework, for testing hypotheses. These systems are here exemplified by the distributed ART (dART) model, which generalizes localist ART systems to allow arbitrarily distributed code representations, while retaining basic capabilities such as stable fast learning and scalability. Since each component is placed in the context of a unified real-time system, analysis can move from the level of neural processes, including learning laws and rules of synaptic transmission, to cognitive processes, including attention and consciousness. Local design is driven by global functional constraints, with each network synthesizing a dynamic balance of opposing tendencies. The self-contained working ART and dART models can also be transferred to technology, in areas that include remote sensing, sensor fusion, and content-addressable information retrieval from large databases.en_US
dc.description.sponsorshipOffice of Naval Research and the defense Advanced Research Projects Agency (N00014-95-1-0409, N00014-1-95-0657); National Institutes of Health (20-316-4304-5)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-2000-010en_US
dc.rightsCopyright 2000 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.subjectAdaptive Resonance Theory (ART)
dc.subjectART
dc.subjectdART
dc.subjectNeural networks
dc.subjectDistributed coding
dc.subjectFast learning
dc.subjectCatastrophic forgetting
dc.subjectVisual cortex
dc.titleAdaptive Resonance: An Emerging Neural Theory of Cognitionen_US
dc.typeTechnical Reporten_US
dc.rights.holderBoston University Trusteesen_US


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