Optimizing Single-Layer Raster Cellular Neural Network Simulator Using Simulated Annealing Technique and RK4(2), RK4(3) and RK 6(4)
O. H. Abdelwahed O. H. Abdelwahed, M. El-Sayed Wahed · International Journal of Scientific Research · 2012
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. Explicit Runge Kutta (RK) methods in the form of pairs of orders p (p -2) provide an attractive means for the solution of initial value problems of first-order differential equations. Most existing RK formulas (single methods as well as pairs) use the minimal number of stages required for achieving a prescribed order. In this article we shall study, in terms of efficiency and reliability, RK pairs of orders p (q). This paper reports an efficient algorithm exploiting the latency properties of Cellular Neural Networks along with numerical integration techniques RK4(2), RK4(3), and RK6(4); simulation results and comparisons are also presented. Optimizing Single-Layer Raster Cellular Neural Network Simulator Using Simulated Annealing Technique and RK4(2), RK4(3) and RK 6(4)