LMI-Based Synchronization Conditions to R-L Fractional Time-Varying Delayed Neural Networks with Parametric Uncertainty

The synchronization conditions to Riemann-Liouville fractional time-varying delayed neural networks with parametric uncertainty are investigated in this article. A novel Lyapunov-Krasovskii functional including double integral terms is proposed, which greatly cutes down on the conservatism about the results. The new synchronization criteria are established and characterized as linear matrix inequalities by using convex combination technique, fractional calculus properties and delay-decomposing method. Finally, two numerical simulations illustrate the correctness of the results.

Automated summary

This article investigates the synchronization conditions of Riemann-Liouville fractional time-varying delayed neural networks with parametric uncertainty. A novel Lyapunov-Krasovskii functional with double integral terms is proposed, which reduces the conservatism of the results. The new synchronization criteria are established and characterized as linear matrix inequalities using convex combination technique, fractional calculus properties, and delay-decomposing method. Finally, two numerical simulations verify the correctness of the results.