Delay‐dependent stability analysis for neural networks with additive time‐varying delay components

This article studies the problem of stability analysis for neural networks (NNs) with two additive time‐varying delay components. By taking both the independence and the variation of the two delay components into consideration, a more general Lyapunov functional is defined. By estimating the upper bound of the derivative of the Lyapunov functional more tightly, a less conservative delay‐dependent stability criterion is established in terms of linear matrix inequalities. To reduce the computational complexity, a method for eliminating slack variables is provided, and then a simplified stability criterion is obtained. Some numerical examples are given to illustrate the effectiveness of the proposed method and the significant improvement over the existing results.