Stochastic finite-time boundedness for Markovian jumping neural networks with time-varying delays

In this paper, a novel method is developed for the finite-time boundedness of Markovian jumping neural networks with time-varying delays. By introducing a newly augmented stochastic Lyapunov–Krasovskii functional and novel activation function conditions, sufficient condition for Markovian jumping neural networks is presented, and the state trajectory remains in a bounded region over a pre-specified finite-time interval. Finally, numerical examples are given to illustrate the efficiency and less conservative of the proposed method.