Pulse width dependent operations of a Ag2S island network reservoir

Abstract

Abstract The rapid growth in demand for edge artificial intelligence increases importance of physical reservoirs that work at low computational cost with low power consumption. A Ag2S island network also works as a physical reservoir, in which various physicochemical phenomena contribute to a reservoir operation. In this study, we investigated its frequency dependence and found that diffusion of Ag+ cations in a Ag2S island, which has a relaxation time of about 100 μs, plays a major role when performance is improved. Modified National Institute of Standards and Technology (MNIST) classification task using an input pulse width of 100 μs resulted in the accuracy of 91%. Iterative operations up to 10 million cycles revealed a small enough standard deviation of output, suggesting a potential for practical use of a Ag2S island network as a reservoir.