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The physical basis of an artificial neuron is studied using a model that is based on the stochastic transition between two states in a double well potential. It is shown… Click to show full abstract
The physical basis of an artificial neuron is studied using a model that is based on the stochastic transition between two states in a double well potential. It is shown that the stochastic transition model generates an energy-defined sigmoid function acting as an activation (or transfer) function in neurons. The model is also applied to circuit neurons using superconducting quantum interference devices in artificial neural networks.The physical basis of an artificial neuron is studied using a model that is based on the stochastic transition between two states in a double well potential. It is shown that the stochastic transition model generates an energy-defined sigmoid function acting as an activation (or transfer) function in neurons. The model is also applied to circuit neurons using superconducting quantum interference devices in artificial neural networks.
Journal Title: Journal of Applied Physics
Year Published: 2018
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