A numerical method for frequency determination in the astable cellular neural networks with opposite-sign templates

dc.contributor.authorÖzmen, Atilla
dc.contributor.authorTander, Baran
dc.date.accessioned2019-06-27T08:06:52Z
dc.date.available2019-06-27T08:06:52Z
dc.date.issued2006
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.description.abstractIn this study a numerical method is proposed to determine the oscillation frequencies in the astable cellular neural networks with opposite-sign templates [1]. This method depends on the training of a multilayer perceptron that uses various template coefficients and the correspondant frequency values as inputs and outputs. First of all a frequency surface is obtained from templates and then training samples are picked from this surface in order to apply to multilayer perceptron. The effects of the template coefficients to the oscillation frequencies are also investigated. Furthermore an oscillator design is carried out for simulation and the performance as well as the advantages of the proposed method are evaluated.en_US]
dc.identifier.citation0
dc.identifier.endpage+
dc.identifier.isbn978-1-4244-0238-0
dc.identifier.scopusqualityN/A
dc.identifier.startpage9en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12469/1238
dc.identifier.wosWOS:000245347800003en_US
dc.identifier.wosqualityN/A
dc.institutionauthorÖzmen, Atillaen_US
dc.institutionauthorTander, Baranen_US
dc.language.isotren_US
dc.publisherIEEEen_US
dc.relation.journal2006 IEEE 14th Signal Processing and Communications Applications, Vols 1 and 2en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleA numerical method for frequency determination in the astable cellular neural networks with opposite-sign templatesen_US
dc.typeConference Objecten_US
dspace.entity.typePublication
relation.isAuthorOfPublicationcf8f9e05-3f89-4ab6-af78-d0937210fb77
relation.isAuthorOfPublication75e36d40-1e6e-401f-b656-5894d3bd22e9
relation.isAuthorOfPublication.latestForDiscoverycf8f9e05-3f89-4ab6-af78-d0937210fb77

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