Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/73160
Campo DC Valoridioma
dc.contributor.authorBenítez-Díaz, Domingoen_US
dc.contributor.authorGarcía Quesada, Jesúsen_US
dc.date.accessioned2020-06-09T17:37:51Z-
dc.date.available2020-06-09T17:37:51Z-
dc.date.issued1995en_US
dc.identifier.isbn978-3-540-59497-0en_US
dc.identifier.issn0302-9743en_US
dc.identifier.otherWoS-
dc.identifier.urihttp://hdl.handle.net/10553/73160-
dc.description.abstractIn this paper a new learning algorithm for Fuzzy Radial Basis Function Neural Networks is presented which is characterized by its fully-supervising, self-organizing and fuzzy properties, with an associated computational cost that is fewer than other algorithms. II is intended for pattern classification tasks, and is capable of automatically configuring the Fuzzy RBF network. The methodology shown here is bused on the self-determination of network architecture and the self-recruitment of nodes with a gaussian type of activation function. i.e. the center and covariance matrices of the activation functions together with the number of tuned and output nodes. This approach consists in a mix of the ''Thresholding in Features Spaces'' techniques rind the updating strategies of the ''Fuzzy Kohonen Clustering Networks'' introducing a Gaussian Membership function. Its properties are the same as those of the traditional membership function used in Furry c-Means clustering algorithms, but with the membership function proposed here it lets a nearer relationship exist between learning algorithm and network architecture. Data from a real image and the results given by the algorithm ore used to illustrate this method.en_US
dc.languageengen_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.sourceMira J., Sandoval F. (eds) From Natural to Artificial Neural Computation. IWANN 1995. Lecture Notes in Computer Science, [ISSN 0302-9743], v. 930, p. 527-534. Springer, Berlin, Heidelberg. (1995)en_US
dc.subject120304 Inteligencia artificialen_US
dc.titleLearning algorithm with Gaussian membership function for Fuzzy RBF neural networksen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conferenceInternational Workshop on Artificial Neural Networksen_US
dc.identifier.doi10.1007/3-540-59497-3_219en_US
dc.identifier.isiA1995BF02K00071-
dc.description.lastpage534en_US
dc.description.firstpage527en_US
dc.relation.volume930en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.contributor.daisngid7544831-
dc.contributor.daisngid16156285-
dc.description.numberofpages8en_US
dc.identifier.eisbn978-3-540-49288-7-
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:BenitezDiaz, D-
dc.contributor.wosstandardWOS:GarciaQuesada, J-
dc.date.coverdate1995en_US
dc.identifier.conferenceidevents121217-
dc.identifier.ulpgces
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.event.eventsstartdate07-06-1995-
crisitem.event.eventsenddate09-06-1995-
crisitem.author.deptGIR SIANI: Modelización y Simulación Computacional-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0003-2952-2972-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNameBenítez Díaz, Domingo Juan-
crisitem.author.fullNameGarcía Quesada, Jesús-
Colección:Actas de congresos
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