Stability of delay neural networks with uncertainties via delayed intermittent control

Abstract

Abstract In this paper, we investigate the stability of neural networks with both time-varying delays and uncertainties. A novel delayed intermittent control scheme is designed to ensure the globally asymptotical stability of the addressed system. Some new delay dependent sufficient criteria for globally asymptotical stability results are derived in term of linear matrix inequalities (LMIs) by using free-weighting matrix techniques and Lyapunov–Krasovskii functional method. Finally, a numerical simulation is provided to show the effectiveness of the proposed approach.

Keywords

• Neural networks
• Delayed intermittent control
• Time-varying delay
• Globally asymptotical stability
• LMIs