Finite-time stability analysis of fractional-order complex-valued memristor-based neural networks with time delays

Synchronization of fractional-order complex-valued neural networks with time delay

“…It should be pointed out that most of the results about complex-valued neural networks are integer-order ones. There are only a few results investigating the dynamics of fractional-order complex-valued neural networks (Rakkiyappan, Cao, & Velmurugan, 2014;. It is well known that synchronization is one of the most important and interesting phenomenon of dynamical systems that exists in natural and man-made systems.…”

Stability and synchronization of memristor-based fractional-order delayed neural networks

“…Finite-time stability of fractional-order complex-valued memristor-based neural networks with time delays was discussed in Ref. (Rakkiyappan, Velmurugan, & Cao, 2014).…”

Stability Analysis of Fractional Order Complex-Valued Memristive Neural Networks with Time Delays

“…In which, Fig. 1 shows the state trajectory of real and imaginary parts of (33). Now, we will show the influence of α, in order to show the influence of α, we choose α = 0.3, and its state trajectories are depicted in Figs can draw the conclusion that the higher of α, the more rapidly of the system will achieve the finite-tim stability.…”

“…To the best of our knowledge, the fractional-order complex-valued one has not been investigated yet in the existing literature. Inspired by the above discussion, based on the works in [30][31][32][33][34][35], in this paper we pay attention to the stability analysis of delayed fractional-order complex-valued memristive neural networks. By means of appropriate Lyapunov functional, nonlinear measure method as well as inequality techniques, some sufficient conditions are shown to ascertain the existence, uniqueness and stability of the equilibrium point for the given fractional order complex-valued systems.…”