Applications of Memristors in Neural Networks and Neuromorphic Computing: A Review

Abstract

Memristor is one of the best choices for neuromorphic computing because of its synapse-like structure and function. The single memristor with ion dynamics enables emulations of diverse synaptic plasticity significant for learning and memory. Moreover, several memristive crossbar arrays show low power consumption, high precision and high efficiency on physically achieving algorithmic functions. Although a large number of experiments have demonstrated great potential of memristive devices in the field of computer architecture design and integrated circuits, there is still a long way to go for their practical industrialization. This review concentrates on the application and function of memristors, as well as some critical challenges and perspectives on their future development.