Finite-time boundedness of state estimation for neural networks with time-varying delays

In this paper, we study the finite-time boundedness problem for neural networks with time-varying delays. By introducing a newly augmented Lyapunov–Krasovskii functional and considering the relationship between time-varying delays and their upper delay bounds, sufficient condition of state estimation for neural networks with time-varying delays is presented and proved by using convex polyhedron method and novel activation function conditions. Finally, a numerical example is given to illustrate the efficiency and less conservative character of the proposed method.