Neural Pattern Recognition on Multichannel Input Representation
| Data(s) |
14/11/2011
14/11/2011
01/01/1993
|
|---|---|
| Resumo |
This article presents a new neural pattern recognition architecture on multichannel data representation. The architecture emploies generalized ART modules as building blocks to construct a supervised learning system generating recognition codes on channels dynamically selected in context using serial and parallel match trackings led by inter-ART vigilance signals. Sharp Corporation, Information Techology Research Laboratories, Nara, Japan |
| Identificador | |
| Idioma(s) |
en_US |
| Publicador |
Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems |
| Relação |
BU CAS/CNS Technical Reports;CAS/CNS-TR-1993-026 |
| Direitos |
Copyright 1993 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. Boston University Trustees |
| Tipo |
Technical Report |
