Novel criterions for global asymptotic stability of static neural networks with time-varying delays

Abstract

In this paper, we investigate the global asymptotic stability of the static neural networks with time-varying delays. Based on the Lyapunov functional method and some free-weighting matrix, two innovative criterions are obtained, which are the significant improvement in the performance. Compared with the former references, our results are less conservative, and the conditions are expressed by linear matrix inequalities, which can be easily computed in MATLAB toolbox. Two numerical examples are provided to illustrate the effectiveness of the proposed result.