%P 147-154
%I Institute of Electrical and Electronics Engineers Inc.
%A A.A. Fida
%A F.A. Khanday
%A F. Zahoor
%A T.Z. Azni Bin Zulkifli
%T Nanoionic Redox based Resistive Switching Devices as Synapse for Bio-inspired Computing Architectures: A Survey
%R 10.1109/ICOEI48184.2020.9142927
%D 2020
%J Proceedings of the 4th International Conference on Trends in Electronics and Informatics, ICOEI 2020
%L scholars13081
%O cited By 3; Conference of 4th International Conference on Trends in Electronics and Informatics, ICOEI 2020 ; Conference Date: 15 June 2020 Through 17 June 2020; Conference Code:161905
%K Biomimetics; Computer architecture, Bio-inspired computing; Biological learning; Biophysical properties; Neuromorphic computing; Nonlinear properties; Resistive switching; Resistive switching devices; Spike timing dependent plasticities, Memristors
%X Neuromemristive circuits represent a new paradigm in the field of neuromorphic computing wherein memristive devices are used as artificial synapses. The primary benefit of these devices is that they take advantage of material properties to emulate the temporal and biophysical properties of biological neural elements. Memristors under their state-dependent non-linear properties can mimic the biological synaptic behavior of co-localized memory and processing abilities. Besides, memristors have also been reported to replicate biological learning rules like spike-timing-dependent plasticity. This paper focuses on one class of memristors based on resistive switching caused by nano ionic redox processes. The operation, classification, and key behaviors are discussed while taking into consideration the key challenges that are encountered in their synaptic implementations. © 2020 IEEE.