具有时延和随机扰动的未知C-G神经网络的有限时间函数投影同步及其在保密通信中的应用
摘要
The finite-time function projective synchronization of unknown Cohen-Grossberg neural networks with time delays and stochastic disturbances was investigated. A hybrid control scheme combining open-loop control and feedback control was designed to guarantee that the drive and response networks can be synchronized up to a scaling function in a finite time with parameter identification by means of the finite-time stability theory. Besides, the upper bounds of the settling time of synchronization were estimated. Finally, the corresponding numerical simulation and its application in secure communication were provided to demonstrate the validity of the presented synchronization method.
引用本文（GB/T 7714）
张雅美，郝涛，尹四倍，张檬, ZHANG Yamei, HAO Tao, 等. 具有时延和随机扰动的未知C-G神经网络的有限时间函数投影同步及其在保密通信中的应用[J]. 应用数学和力学, 2020.
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