The vector-matrix form numerical simulations for time-derivative cellular neural networks

Abstract

Time-derivative cellular neural network (TDCNN) state equations can be written in vector-matrix form which enables the application of discrete-time numerical simulation methods. In this paper, existing numerical simulation methods are adapted for TDCNN for the first time, namely, MATLAB ordinary differential equation simulation and the vector-matrix fourth-order Runge-Kutta approximation. Afterwards, several simulation methods for TDCNN are analyzed. The ordinary differential equation solvers in MATLAB program, fourth-order Runge-Kutta approximation, and the forward Euler approximation are used in the numerical simulation of the vector-matrix form TDCNN. Our previously proposed fast simulation method for TDCNNs is revisited. The methods are discussed from a programmer's point of view, and the results are presented.