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- W2076800810 abstract "Chaotic neural networks are able to reproduce chaotic dynamics observable in the brain of various living beings. As a result, study of the dynamical properties of such networks may pave the way towards a better understanding of the memory rules of the brain. In this paper a simple neural circuit employing a theoretical memristive synapse with symmetric charge-flux nonlinearity is found to behave chaotically. After presentation of a novel boundary-condition based model for real memristor nano-structures, conditions under which a suitable arrangement of such nano-structures is dynamically equivalent to the theoretical memristor are derived and validated." @default.
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- W2076800810 date "2012-06-01" @default.
- W2076800810 modified "2023-09-27" @default.
- W2076800810 title "Memristor models for chaotic neural circuits" @default.
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- W2076800810 doi "https://doi.org/10.1109/ijcnn.2012.6252777" @default.
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