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- W4385482977 abstract "An ergodic sequential logic (SL) neuron model is designed and it is shown that the model can reproduce various nonlinear responses of neurons. Using the neuron model, a novel ergodic SL spiking neural network is presented. It is shown that the network can reproduce biologically plausible spatio-temporal phenomena, (e.g., fundamental synchronization phenomenon and complicated chimera phenomenon) which are typically observed in the brain. In addition, the network is implemented by a field programmable gate array and it is shown that the presented network is more hardware-efficient compared to a commonly used digital processor spiking neural network. Furthermore, it is discussed that the presented network will contribute to develop a small and low power brain prosthetic device." @default.
- W4385482977 created "2023-08-03" @default.
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- W4385482977 date "2023-06-18" @default.
- W4385482977 modified "2023-09-26" @default.
- W4385482977 title "A novel hardware-efficient ergodic sequential logic spiking neural network and reproductions of biologically plausible spatio-temporal phenomena towards development of neural prosthetic device" @default.
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- W4385482977 doi "https://doi.org/10.1109/ijcnn54540.2023.10191905" @default.
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