Review of memristor based neuromorphic computation: opportunities, challenges and applications

Abstract

Abstract The memristor is regarded as one of the promising possibilities for next-generation computing systems due to its small size, easy construction, and low power consumption. Memristor-based novel computing architectures have demonstrated considerable promise for replacing or enhancing traditional computing platforms that encounter difficulties in the big-data era. Additionally, the striking resemblance between the mechanisms governing the programming of memristance and the manipulation of synaptic weight at biological synapses may be used to create unique neuromorphic circuits that function according to biological principles. Nevertheless, getting memristor-based computing into practice presents many technological challenges. This paper reviews the potential for memristor research at the device, circuit, and system levels, mainly using memristors to demonstrate neuromorphic computation. Here, the common issues obstructing the development and widespread use of memristor-based computing systems are also carefully investigated. This study speculates on the prospective applications of memristors, which can potentially transform the field of electronics altogether.