A π-Type Memristor Synapse and Neuron With Structural Plasticity

Abstract

A synaptic structure with memristor state initialization function and a neuronal circuit with structural variability are presented in this article. In contrast to the popular use of voltage as a medium for containing information and realizing the computational function of a neuron in the form of voltage–current–voltage, the proposed neuron circuit adopts current as a carrier of information; also the computation will be realized in the form of current–voltage instead. Since the sum of currents can be achieved by direct connection, this will greatly reduce the hardware area of the artificial neuron. In addition, by adjusting the switches, the initialization of the memristor can be implemented, and the process of structural changes of neurons in biology can also be mimicked. Comparing with several popular synaptic circuits, it is proven that the π-type synapse has more structural advantages. Simulations show that the π-type synaptic structure can obtain the specified weight value faster and complete the initial state setting of the memristors in 1.502 ms. Even in the worst case, where the weight needs to be changed from −1 to 1, it can be completed in only 1.272 ms. Under the condition of achieving the same function, the area of the proposed neuron with 100 synapses will be reduced by at least 97.42%. Moreover, there is better performance in terms of linearity.