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Synchrony based learning rule of Hopfield like chaotic neural networks with desirable structure

In this paper a new learning rule for the coupling weights tuning of Hopfield like chaotic neural networks is developed in such a way that all neurons behave in a synchronous manner, while the desirable structure of the network is preserved during the learning process. The proposed learning rule is...

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Detaylı Bibliyografya
Asıl Yazarlar: Mahdavi, Nariman, Kurths, Jürgen
Materyal Türü: Artigo
Dil:Inglês
Baskı/Yayın Bilgisi: Springer Netherlands 2013
Konular:
Online Erişim:https://ncbi.nlm.nih.gov/pmc/articles/PMC3945457/
https://ncbi.nlm.nih.gov/pubmed/24624234
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s11571-013-9260-2
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