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Experimental study demonstrates high endurance and synaptic plasticity in halide perovskite crossbar memristors, indicating viable hardware for artificial neural networks.
s) and high endurance (2000 cycles). Finally, we put forth a universal approach to comprehensively map the analog programming window of halide perovskite memristive devices - a critical prerequisite for weighted synaptic connections in artificial neural networks. This consequently facilitates the demonstration of accurate handwritten digit recognition from the MNIST database based on spike-timing-dependent plasticity of halide perovskite memristive synapses.
Vishwanath et al. (2024) studied this question.