一种反向串联忆阻突触电路的设计及应用
摘要
The memory effect of memristors is similar to a synaptic in neuromorphic systems. It will be of great significance for a neuromorphic system that memristors have nanoscale size, low-power consumption, and high integration, which give the memristive synapse more intelligent information processing ability. On the basis of an improved memristor model, this paper addresses a switching synaptic circuit with two memristors in reverse series. When the switch is off, the input square-wave voltage is used to adjust the synaptic weight. When the switch is on, the memristance in the circuit is used to store information. This synapse circuit has a spike-time-dependent-plasticity (STDP) bionic learning ability and continuous linear resistance characteristics. In this study, the synapse circuit is introduced to a memristive crossbar array to store images. We optimize storage solutions, discuss the impact of the noise voltage of image storage, and conduct a comparison of numerical analysis and analog simulation. Experimental results show that the proposed storage solution is more reliable and robust than single-memristor cross-array storage.