Impulsive Time Window-Based Saturation Impulsive Synchronization of Coupled Neural Networks
研究了具有比例时滞和分布时滞的有向耦合神经网络在脉冲时间窗方案下的饱和分布式脉冲局部指数同步问题，通过凸包表示和脉冲比较原理给出了同步的充分条件，并优化了脉冲控制增益以扩大吸引域估计。
This article considers the saturated distributed impulsive local exponential synchronization (LES) issue for directed coupled neural networks (CNNs) with proportional delay and distributed delay under the impulsive time window (ITW) scheme. By utilizing a modified compact convex hull representation of the saturation nonlinearity, the extended parameter variation formula, and the proportional delayed impulsive comparison principle, sufficient conditions for the local exponential synchronization (LES) of the CNNs subject to actuator saturation are obtained within the domain of attraction (DOA). Based on these conditions, an optimization problem constructed by transformed linear matrix inequality (LMI) constraints is formulated to determine the impulsive control gain for enlarging the estimation of DOA as much as possible with a predetermined exponential convergence rate. Ultimately, a numerical simulation is exhibited to illustrate the feasibility and validity of the theoretical results.