Stability and Hopf bifurcation analysis of fractional-order complex-valued neural networks with time delays

• Main Authors: R Rakkiyappan, K Udhayakumar, G Velmurugan, Jinde Cao, Ahmed Alsaedi
• Format: Article
• Language: English
• Published: SpringerOpen 2017-08-01
• Series: Advances in Difference Equations
• Subjects: Hopfield neural networks; fractional-order; time delays; hub structure; ring structure; stability
• Online Access: http://link.springer.com/article/10.1186/s13662-017-1266-3

Abstract This paper considers a class of fractional-order complex-valued Hopfield neural networks (CVHNNs) with time delay for analyzing the dynamic behaviors such as local asymptotic stability and Hopf bifurcation. In the case of a neural network with hub and ring structure, the stability of the equilibrium state is investigated by analyzing the eigenvalue of the corresponding characteristic matrix for the hub and ring structured fractional-order time delay models using a Laplace transformation for the Caputo-fractional derivatives. Some sufficient conditions are established to guarantee the uniqueness of the equilibrium point. In addition, conditions for the occurrence of a Hopf bifurcation are also presented. Finally, numerical examples are given to demonstrate the effectiveness of the derived results.