Global Asymptotical Stability Analysis for Fractional Neural Networks with Time-Varying Delays

Abstract

In this paper, the global asymptotical stability of Riemann-Liouville fractional-order neural networks with time-varying delays is studied. By combining the Lyapunov functional function and LMI approach, some sufficient criteria that guarantee the global asymptotical stability of such fractional-order neural networks with both discrete time-varying delay and distributed time-varying delay are derived. The stability criteria is suitable for application and easy to be verified by software. Lastly, some numerical examples are presented to check the validity of the obtained results.

Keywords

• time-varying delay
• global asymptotical stability
• fractional-order
• neural networks
• linear matrix inequality