Exponential stability of delay dependent neutral-type descriptor neural networks with uncertain parameters

Abstract

The idea of delay-dependent states of neutral-type uncertain descriptor neural networks with mixed delays in time-varying sense (i.e. discrete & distributed) and leakage delays is implemented in this study. By building a modern LKF (Lyapunov–Krasovskii functional) and enlisting some analysis techniques, new stability conditions for the designated neural networks are derived in terms of linear matrix inequalities (LMIs), which can be easily verified by the MATLAB LMI toolbox. To do that, the research that is being offered here is more advanced and less constrained than the previous one that has been published in the literature. Two numerical examples with simulations and some novel comparative statements are carried out to demonstrate the benefit and validity of our theoretical conclusions.

Keywords

• Exponentially stable
• Neutral type neural networks
• Linear matrix inequality
• Time-varying delays