An efficient numerical integration algorithm for single-layer Raster cellular neural networks simulator

Abstract

An efficient numerical integration algorithm for single layer Raster cellular neural networks(CNN) simulator is presented in this paper. The simulator is capable of performing 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 CNN along with numerical integration techniques; these numerical integration techniques are Euler, Runge Kutta fourth-second order 4(2), and Runge Kutta fourth-third order 4(3). Simulation results and comparisons are also presented. Comparisons include CPU time, quality measures of the pictures used in comparison, step size used, the format of input pictures. The CPU time used here is the simulation time. Key words: Single-layer cellular neural networks, numerical integration algorithms, RK 4(2), RK 4(3).