Resistive Switching-based Neuromorphic Devices for Artificial Neural Networks

The integration of software- and hardware-based brain computing is attracting attention to develop future artificial neural network systems. In this chapter, we have discussed materials modification, device engineering, sensory neuro-electronics, and flexible memristor devices for ANNs. Moreover, the basic properties of brain computing such as potentiation, depression, STDP, and SRDP have been discussed by modulating electrical stimuli like the amplitude and width of the applied pulse as well as sensory effects like optical stimuli and mechanical pressure (tactile stimuli). The effect of active materials and electrodes on neuromorphic properties has been discussed through various mechanisms such as charge transport, ferroelectric effects, ionic drift, and movement of oxygen vacancies. Hence, this chapter provides a way for the future advancement of memristive devices in artificial neural network (ANN) systems.