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dc.contributor.authorBolouri, H.
dc.contributor.authorAdams, R.G.
dc.contributor.authorGeorge, S.
dc.contributor.authorRust, A.G.
dc.date.accessioned2009-10-21T11:22:58Z
dc.date.available2009-10-21T11:22:58Z
dc.date.issued1998
dc.identifier.citationBolouri , H , Adams , R G , George , S & Rust , A G 1998 , Molecular self-organisation in a developmental model for the evolution of large-scale artificial neural networks . in Proceedings of the 1998 International Conference on Neural Information Processing and Intelligent Information Systems (ICONIP'98) . vol. 2 , pp. 797-800 .
dc.identifier.otherPURE: 406728
dc.identifier.otherPURE UUID: bce39bed-33c8-48fb-8d57-2b39492bd1b0
dc.identifier.otherdspace: 2299/3983
dc.identifier.urihttp://hdl.handle.net/2299/3983
dc.description.abstractWe argue that molecular self-organisation during embryonic development allows evolution to perform highly nonlinear combinatorial optimisation. A structured approach to architectural optimisation of large-scale Artificial Neural Networks using this principle is presented. We also present simulation results demonstrating the evolution of an edge detecting retina using the proposed methodology.en
dc.language.isoeng
dc.relation.ispartofProceedings of the 1998 International Conference on Neural Information Processing and Intelligent Information Systems (ICONIP'98)
dc.titleMolecular self-organisation in a developmental model for the evolution of large-scale artificial neural networksen
dc.contributor.institutionCentre for Computer Science and Informatics Research
dcterms.dateAccepted1998
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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