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• W3091420610 abstract "We present simulations based on a model of self- assembled nanowire networks with memristive junctions and neural network-like topology. We analyze the dynamical voltage distribution in response to an applied bias and explain the network conductance fluctuations observed in our previous experimental studies. We then demonstrate the potential of neuromorphic nanowire networks as a physical reservoir by performing benchmark reservoir computing tasks. The tasks include sine wave nonlinear transformation, sine wave auto- generation and forecasting the Mackey-Glass chaotic time series." @default.
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• W3091420610 date "2020-07-01" @default.
• W3091420610 modified "2023-09-30" @default.
• W3091420610 title "Reservoir Computing with Neuromemristive Nanowire Networks" @default.
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• W3091420610 doi "https://doi.org/10.1109/ijcnn48605.2020.9207727" @default.
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