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, cilt.28, sa.6, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 28 Sayı: 6
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1142/s0218127418300197
  • Dergi Adı: INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Anahtar Kelimeler: State Controlled-Cellular Neural Networks, multivariable nonlinearities, complex dynamics, CELLULAR NEURAL-NETWORKS, CIRCUIT
  • Sivas Cumhuriyet Üniversitesi Adresli: Evet

Özet

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.