Rk Starters for Multistep Methods on Hole-filler Cnn Simulation

The goal of this paper is focused on developing an efficient design strategy for simulating CNN arrays and hole-filling is implemented using RK step multistep methods to improve the performance of the image or handwritten character recognition. This approach is carried out by analyzing the important features of the hole-filler template and the dynamic process of CNN using well knownr RK step multistep methods to obtain a set of inequalities satisfying its output characteristics as well as the parameter range of the hole-filler template. Simulation results and comparison have also been presented to show the efficiency of the Numerical Integration Algorithms. In this article, the use of new improved fourth and fifth order linear and nonlinear Runge-Kutta methods in starting procedures for the well known RK step multistep methods is adapted to yield greater accuracy compared with using the standard fourth order Runge-kutta method in the application to problems involving discontinuities and severe gradients where the stepsize is frequently changed.