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


Polat S. N.

INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS, vol.31, no.5, 2018 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 31 Issue: 5
  • Publication Date: 2018
  • Doi Number: 10.1002/jnm.2328
  • Title of Journal : INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS

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.