Finite-Time Projective Synchronization of Caputo Type Fractional Complex-Valued Delayed Neural Networks

Abstract

This paper focuses on investigating the finite-time projective synchronization of Caputo type fractional-order complex-valued neural networks with time delay (FOCVNNTD). Based on the properties of fractional calculus and various inequality techniques, by constructing suitable the Lyapunov function and designing two new types controllers, i.e., feedback controller and adaptive controller, two sufficient criteria are derived to ensure the projective finite-time synchronization between drive and response systems, and the synchronization time can effectively be estimated. Finally, two numerical examples are presented to verify the effectiveness and feasibility of the proposed results.

Stability Analysis of Delayed Neural Networks via Composite-Matrix-Based Integral Inequality

“…Moreover, it can further seen that γ can increase the flexibility of the stability condition. It should be pointed out the CMBII can be also applied to the synchronization of time-varying neural networks such as [32,33], which have not considered the delay derivative information.…”