Fractional-order Memcapacitor Bridge Synapse-Based Neural Network

Recently, different neural network models and synapse models have been introduced by significant laboratories worldwide. The research on mem-elements is a promising branch of research due to their natural symmetry with synapses. Nevertheless, neuromorphic computing with memcapacitor is still in its infancy, especially when fractional-order memcapacitor is considered. Fractional-order memcapacitor bridge synapse-based neural network and its dynamic behavior are utterly uncharted territory. The mode of action in the synaptic dynamical state and topological structure of the neural network needs to be thoroughly analyzed. This paper shows the saturation process of fractional-order memcapacitor bridge synapse by using a general fractional-order memcapacitor model. The role of fractional-order in the dynamic transformation of neural network weights is discussed. The influence of fractional-order is quantitatively analyzed, and a kind of simple neural network circuit topology is proposed.