Abstract
In this paper, a three dimensional discrete time Hopfield neural network with commensurate fractional variable order is presented based on the Caputo like difference operator. The dynamics of the proposed system is investigated by means of chaotic attractors, bifurcation diagram and maximum Lyapunov exponents, It is shown that the discrete time Hopfield neural network has complex behaviour for several fractional variable orders and different system parameter values. Moreover, the approximate entropy and the C <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</inf> complexity algorithms of the system are performed to prove the existence of chaos. Finally, the corresponding simulations are carried out on Matlab to illustrate the theoretical results.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
