Li Ning, Cao Jinde, Alsaedi Ahmed, Alsaadi Fuad
College of Mathematics and Information Science, Henan University of Economics and Law, Zhengzhou 450046, Henan, China
School of Mathematics, and Research Center for Complex Systems and Network Sciences Southeast University, Nanjing 210096, China, and Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Neural Comput. 2017 Jun;29(6):1721-1744. doi: 10.1162/NECO_a_00918. Epub 2017 Apr 14.
This letter focuses on lag synchronization control analysis for memristor-based coupled neural networks with parameter mismatches. Due to the parameter mismatches, lag complete synchronization in general cannot be achieved. First, based on the [Formula: see text]-measure method, generalized Halanay inequality, together with control algorithms, some sufficient conditions are obtained to ensure that coupled memristor-based neural networks are in a state of lag synchronization with an error. Moreover, the error level is estimated. Second, we show that memristor-based coupled neural networks with parameter mismatches can reach lag complete synchronization under a discontinuous controller. Finally, two examples are given to illustrate the effectiveness of the proposed criteria and well support theoretical results.
本文聚焦于具有参数失配的基于忆阻器的耦合神经网络的滞后同步控制分析。由于参数失配，一般无法实现滞后完全同步。首先，基于[公式：见原文]测度方法、广义哈莱奈不等式以及控制算法，得到了一些充分条件，以确保基于忆阻器的耦合神经网络处于具有误差的滞后同步状态。此外，还对误差水平进行了估计。其次，我们表明具有参数失配的基于忆阻器的耦合神经网络在不连续控制器作用下能够达到滞后完全同步。最后，给出两个例子来说明所提准则的有效性，并很好地支持了理论结果。
