Improved exponential stability criteria for neural networks with time-varying delays

This paper concerned the problem of exponential stability criteria for neural networks with discrete and distributed time-varying delays. By dividing the delay interval into multiple segments and choosing a new Lyapunov functional, some improved stability criteria are derived in terms of linear matrix inequalities. The obtained criteria are less conservative due to a convex optimization approach is considered. Finally, two numerical examples are given to illustrate the effectiveness of the proposed method.