Abstraction in Fpga Implementation of Neural Networks

gdc.relation.journal Proceedings Of The 9th Wseas International Conference On Neural Networks (Nn' 08): Advanced Topics On Neural Networks en_US
dc.contributor.author Öğrenci, Arif Selçuk
dc.contributor.other 01. Kadir Has University
dc.date.accessioned 2019-06-27T08:06:19Z
dc.date.available 2019-06-27T08:06:19Z
dc.date.issued 2008
dc.description.abstract A model for FPGA implementation of multilayer perceptron neural networks is presented. The model tries to incorporate object oriented design principles in the analysis training and design of components using hardware description languages. The synthesis will be based on the tools supplied by the FPGA vendors. The results indicate that the method can be utilized and it can be further improved to create a general methodology that bridges the gap between hardware and software in embedded system design. en_US]
dc.identifier.citationcount 0
dc.identifier.isbn 978-960-6766-56-5
dc.identifier.uri https://hdl.handle.net/20.500.12469/1182
dc.identifier.uri http://www.wseas.us/e-library/conferences/2008/sofia/NN/nn36.pdf
dc.language.iso en en_US
dc.publisher World Scientific and Engineering Academy and Society en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Hardware synthesis en_US
dc.subject Software architecture en_US
dc.title Abstraction in Fpga Implementation of Neural Networks en_US
dc.type Conference Object en_US
dspace.entity.type Publication
gdc.author.institutional Öğrenci, Arif Selçuk en_US
gdc.coar.access open access
gdc.coar.type text::conference output
gdc.description.department Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü en_US
gdc.description.endpage 224
gdc.description.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
gdc.description.startpage 221 en_US
gdc.identifier.wos WOS:000257699300040 en_US
gdc.wos.citedcount 0
relation.isOrgUnitOfPublication b20623fc-1264-4244-9847-a4729ca7508c
relation.isOrgUnitOfPublication.latestForDiscovery b20623fc-1264-4244-9847-a4729ca7508c

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