Switched State Controlled-CNN: An Alternative Approach in Generating Complex Systems with Multivariable Nonlinearities Using CNN


GÜNAY E., ALTUN K.

INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, vol.28, no.6, 2018 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 28 Issue: 6
  • Publication Date: 2018
  • Doi Number: 10.1142/s0218127418300197
  • Title of Journal : INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS

Abstract

It has been already shown in the literature that extended State Controlled-Cellular Neural Network (SC-CNN) could be used to approximate the behavior of complex dynamics with multivariable nonlinearities by modifying the nonlinearity. In this study, a different approach to imitating the multivariable nonlinearities in complex dynamical systems by switching the states of SC-CNN is given. For this purpose, first of all, Rossler type system dynamics are generated by switching the states of Cellular Neural Networks (CNNs). In the second study, Sprott-94-f type system is presented. All systems are numerically and experimentally investigated in order to verify the convenience of the standpoint.