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dc.contributor.authorRust, A.G.
dc.contributor.authorAdams, R.G.
dc.contributor.authorGeorge, S.
dc.contributor.authorBolouri, H.
dc.date.accessioned2009-10-20T13:06:49Z
dc.date.available2009-10-20T13:06:49Z
dc.date.issued2001
dc.identifier.citationRust , A G , Adams , R G , George , S & Bolouri , H 2001 , ' Towards Computational Neural Systems through Developmental Evolution ' , Lecture Notes in Computer Science , vol. 2036 , pp. 188-202 . https://doi.org/10.1007/3-540-44597-8
dc.identifier.issn0302-9743
dc.identifier.otherPURE: 94997
dc.identifier.otherPURE UUID: 2b572182-158c-41b4-8815-5f538b28d470
dc.identifier.otherdspace: 2299/3976
dc.identifier.urihttp://hdl.handle.net/2299/3976
dc.description“The original publication is available at www.springerlink.com”. Copyright Springer. DOI: 10.1007/3-540-44597-8_14 [Full text of this article is not available in the UHRA]
dc.description.abstractThe capability of creating artificial neural networks with biologically-plausible characteristics, is becoming ever more attainable through the greater understanding of biological neural systems and the constant increases in available desktop computing power. Designing and implementing such neural systems still however remains a complex and challenging problem. This chapter introduces a design methodology, inspired by embryonic neural development, which is capable of creating 3 dimensional morphologies of both individual neurons and networks. Examples of such morphologies are given, which are created by evolving the parameters of the developmental model using an evolutionary algorithm.en
dc.language.isoeng
dc.relation.ispartofLecture Notes in Computer Science
dc.titleTowards Computational Neural Systems through Developmental Evolutionen
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.description.statusPeer reviewed
dcterms.dateAccepted2001
rioxxterms.versionofrecordhttps://doi.org/10.1007/3-540-44597-8
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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