Exponential stabilisation analysis of a class of delayed inertial memristive neural networks
Jiemei Zhao, Zhuoyi Zhang, Dongliang Yang
Abstract
This paper focuses on the exponential stabilisation problem of inertial memristive neural networks (IMNNs) with unbounded discrete time-varying delays. The considered IMNNs are modelled by second-order derivatives equations by introducing the inertial terms. By using nonsmooth analysis, Lyapunov stability theory, inequality techniques and integral-differential of Lyapunov functional method, a feedback controller is designed to guarantee pth moment exponential stabilisation of the addressed IMNNs under the framework of Filippov solutions. It is worth noticing that the considered time delays of IMNNs can be unbounded. Finally, a numerical example is presented to illustrate the effectiveness of the main theoretical result.