Single-layer CNN simulator

Abstract
An efficient behavioral simulator for Cellular Neural Networks (CNN) is presented in this paper. The simulator is capable of performing Single-Layer CNN simulations for any size of input image, thus a powerful tool for researchers investigating potential applications of CNN. This paper reports an efficient algorithm exploiting the latency properties of Cellular Neural Networks along with numerical integration techniques; simulation results and comparisons are also presented

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