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dc.contributor.authorCampos, Marcosen_US
dc.contributor.authorCarpenter, Gail A.en_US
dc.date.accessioned2011-11-14T19:07:57Z
dc.date.available2011-11-14T19:07:57Z
dc.date.issued1998-06en_US
dc.identifier.urihttp://hdl.handle.net/2144/2359
dc.description.abstractThis paper introduces CSOM, a distributed version of the Self-Organizing Map network capable of generating maps similar to those created with the original algorithm. Due to the continuous nature of the mapping, CSOM outperforms the traditional SOM algorithm in function approximation tasks. System performance is illustrated with three examples.en_US
dc.language.isoen_USen_US
dc.publisherBoston University Center for Adaptive Systems and Department of Cognitive and Neural Systemsen_US
dc.relation.ispartofseriesBUCAS/CNS Technical Reports; BUCAS/CNS-TR-1998-025en_US
dc.rightsCopyright 1998 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.titleBuilding Adaptive Basis Functions with a Continuous SOMen_US
dc.typeTechnical Reporten_US
dc.rights.holderBoston University Trusteesen_US


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