Mixed time-delays dependent exponential stability for uncertain stochastic high-order neural networks

This paper presents a discrete and distributed time-delays dependent simultaneous approach to deterministic and uncertain stochastic high-order neural networks. New results are proposed in terms of linear matrix inequality (LMI) by exploiting a novel Lyapunov–Krasovskii functional and by making use of novel techniques for time-delay systems. Some constraints of systems are removed, and new results cover some recently published works. Two numerical examples are given to show the usefulness of presented approach.