Global Asymptotic Stability of Switched Neural Networks with Delays

Abstract EN

This paper investigates the global asymptotic stability of a class of switched neural networks with delays.

Several new criteria ensuring global asymptotic stability in terms of linear matrix inequalities (LMIs) are obtained via Lyapunov-Krasovskii functional.

And here, we adopt the quadratic convex approach, which is different from the linear and reciprocal convex combinations that are extensively used in recent literature.

In addition, the proposed results here are very easy to be verified and complemented.

Finally, a numerical example is provided to illustrate the effectiveness of the results.