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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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| Главные авторы: | , |
|---|---|
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Springer Netherlands
2013
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| Предметы: | |
| Online-ссылка: | 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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