Mean-square Input-to-state Stability for Stochastic Complex-Valued Neural Networks with Neutral Delay

In this paper, the issue of input-to-state exponential stability (ISES) for stochastic complex-valued neural networks with neutral delay (SCVNNs) and discrete delay is considered. Without separating the SCVNNs into two real-valued systems, two criteria expressed through linear matrix inequality (LMI) to pledge ISES of the considered SCVNNs are derived based on Itô formula in complex-valued field, Lyapunov–Krasovskii functional approach as well as some relevant inequality skills. Two examples are furnished to verify the raised results.