Exponential Stabilization of Fuzzy Memristive Neural Networks With Multiple Time Delays Via Intermittent Control
研究了通过间歇控制策略实现具有多时变时滞的T-S模糊忆阻神经网络的全局指数镇定，利用微分包含和比较方法推导了充分条件，并推广到无限分布时滞情形。
This article investigates global exponential stabilization (GES) of Takagi–Sugeno (T–S) fuzzy memristive neural networks with multiple time-varying delays (DFMNNs) via intermittent control strategy. By resorting to differential inclusion theory, comparison means, and inequality techniques, some results are developed to ensure GES of the underlying DFMNNs via a fuzzy intermittent state feedback control law within the sense of Filippov. The outcome is generalized to GES of FMNNs with infinite distributed time delays. Additionally, the global exponential stability of FMNNs with discrete time-varying delays is explored in terms of 1-norm. The derived conditions herein contain certain existing ones as special cases. Finally, three examples are presented to illuminate the validness of the outcomes.