DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Geehyuk | ko |
dc.contributor.author | Yi, Gwan-Su | ko |
dc.date.accessioned | 2013-03-08T14:11:50Z | - |
dc.date.available | 2013-03-08T14:11:50Z | - |
dc.date.created | 2012-06-28 | - |
dc.date.created | 2012-06-28 | - |
dc.date.issued | 2007 | - |
dc.identifier.citation | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.4492 LNCS, no.PART 2, pp.104 - 112 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | http://hdl.handle.net/10203/93220 | - |
dc.description.abstract | The parametrically coupled map lattice (PCML) exhibits many interesting dynamical behaviors that are reminiscent of the adaptation and the learning of the neural network. In order for the PCML to be a model of the neural network, however, it is necessary to identify the biological counterpart of one-dimensional maps that constitute the PCML. One of the possible candidates is a netlet, a small population of randomly interconnected neurons, that was suggested to be a functional unit constituting the neural network. We studied the possibility of representing a netlet by a chaotic one-dimensional map and the result is the chaotic netlet map that we introduce in this paper. © Springer-Verlag Berlin Heidelberg 2007. | - |
dc.language | English | - |
dc.publisher | Springer Verlag | - |
dc.title | The chaotic netlet map | - |
dc.type | Article | - |
dc.identifier.scopusid | 2-s2.0-37249048917 | - |
dc.type.rims | ART | - |
dc.citation.volume | 4492 LNCS | - |
dc.citation.issue | PART 2 | - |
dc.citation.beginningpage | 104 | - |
dc.citation.endingpage | 112 | - |
dc.citation.publicationname | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.contributor.localauthor | Lee, Geehyuk | - |
dc.contributor.localauthor | Yi, Gwan-Su | - |
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