Spiking neural networks (SNNs) are artificial neural networks that more closely mimic natural neural networks.
Spiking neural networks (SNN) integrate the notion of time into their operational model.
The neurons in the spiking neural network (SNN) do not fire on every propagation cycle as with multilayer perceptron networks.
The neurons of the spiking neural network (SNN) fire when a membrane potential which is an intrinsic quality of the neuron reaches a specific value.
When a neuron is triggered, it generates a signal which propagates towards the other neurons which increase or decrease their potential according to the signal received.
In the context of spiking neural networks (SNN), the activation level is modeled as a differential equation which is normally considered as the state of the neuron.
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