A Low-Power Current Mode Fuzzy-ART Cell

Serrano Gotarredona, María Teresa; Linares Barranco, Bernabé

doi:10.1109/TNN.2006.883725

Artículo

dc.creator	Serrano Gotarredona, María Teresa	es
dc.creator	Linares Barranco, Bernabé	es
dc.date.accessioned	2020-09-30T08:10:08Z
dc.date.available	2020-09-30T08:10:08Z
dc.date.issued	2006
dc.identifier.citation	Serrano Gotarredona, M.T. y Linares Barranco, B. (2006). A Low-Power Current Mode Fuzzy-ART Cell. IEEE Transactions on Neural Networks, 17 (6), -1666.
dc.identifier.issn	1045-9227	es
dc.identifier.uri	https://hdl.handle.net/11441/101596
dc.description.abstract	This paper presents a very large scale integration (VLSI) implementation of a low-power current-mode fuzzy-adaptive resonance theory (ART) cell. The cell is based on a compact new current source multibit memory cell with online learning capability. A small prototype of the designed cell and its peripheral block has been fabricated in the AustriaMicroSystems (AMS)-0.35- m technology. The cell occupies a total area of 44 34 m and consumes a maximum current of 22 nA.	es
dc.format	application/pdf	es
dc.format.extent	1673	es
dc.language.iso	eng	es
dc.publisher	IEEE Computer Society	es
dc.relation.ispartof	IEEE Transactions on Neural Networks, 17 (6), -1666.
dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 Internacional	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	*
dc.subject	Adaptive resonance theory (ART)	es
dc.subject	Hardware implementations	es
dc.subject	Low power	es
dc.title	A Low-Power Current Mode Fuzzy-ART Cell	es
dc.type	info:eu-repo/semantics/article	es
dcterms.identifier	https://ror.org/03yxnpp24
dc.type.version	info:eu-repo/semantics/submittedVersion	es
dc.rights.accessRights	info:eu-repo/semantics/openAccess	es
dc.contributor.affiliation	Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores	es
dc.relation.publisherversion	https://ieeexplore.ieee.org/document/4012042	es
dc.identifier.doi	10.1109/TNN.2006.883725	es
dc.journaltitle	IEEE Transactions on Neural Networks	es
dc.publication.volumen	17	es
dc.publication.issue	6	es
dc.publication.endPage	1666	es
dc.identifier.sisius	6628406	es

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