同步(交流)
计算机科学
理论(学习稳定性)
人工神经网络
算法
应用数学
人工智能
数学
机器学习
电信
频道(广播)
作者
Fengshun Wu,Yanli Huang
出处
期刊:Neurocomputing
[Elsevier BV]
日期:2022-01-01
卷期号:469: 163-179
被引量:19
标识
DOI:10.1016/j.neucom.2021.10.067
摘要
In this paper, finite-time synchronization and H∞ synchronization of coupled complex-valued memristive neural networks (CCVMNNs) with or without parameter uncertainty are analyzed. First, a finite-time synchronization (FTS) condition is presented for CCVMNNs by means of deploying Lyapunov stability theory and developing suitable controllers. Then, we utilize the similar method to derive a criterion of robust finite-time synchronization (RFTS) for the proposed CCVMNNs with uncertain parameter. Furthermore, we establish some criteria for the sake of ensuring that the considered network can reach finite-time H∞ synchronization and robust finite-time H∞ synchronization. At last, two numerical examples with simulations demonstrate the validity of the acquired results.
科研通智能强力驱动
Strongly Powered by AbleSci AI