Your browser doesn't support javascript.
loading
Dominant Attractor in Coupled Non-Identical Chaotic Systems.
Nezhad Hajian, Dorsa; Parthasarathy, Sriram; Parastesh, Fatemeh; Rajagopal, Karthikeyan; Jafari, Sajad.
Afiliação
  • Nezhad Hajian D; Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran 159163-4311, Iran.
  • Parthasarathy S; Centre for Computational Modelling, Chennai Institute of Technology, Chennai 600069, Tamil Nadu, India.
  • Parastesh F; Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran 159163-4311, Iran.
  • Rajagopal K; Centre for Nonlinear Systems, Chennai Institute of Technology, Chennai 600069, Tamil Nadu, India.
  • Jafari S; Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran 159163-4311, Iran.
Entropy (Basel) ; 24(12)2022 Dec 11.
Article em En | MEDLINE | ID: mdl-36554212
ABSTRACT
The dynamical interplay of coupled non-identical chaotic oscillators gives rise to diverse scenarios. The incoherent dynamics of these oscillators lead to the structural impairment of attractors in phase space. This paper investigates the couplings of Lorenz-Rössler, Lorenz-HR, and Rössler-HR to identify the dominant attractor. By dominant attractor, we mean the attractor that is less changed by coupling. For comparison and similarity detection, a cost function based on the return map of the coupled systems is used. The possible effects of frequency and amplitude differences between the systems on the results are also examined. Finally, the inherent chaotic characteristic of systems is compared by computing the largest Lyapunov exponent. The results suggest that in each coupling case, the attractor with the greater largest Lyapunov exponent is dominant.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article