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

张雅美; 郝涛; 尹四倍; 张檬

doi:10.21656/1000-0887.410025

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

doi: 10.21656/1000-0887.410025

¹山东劳动职业技术学院电气及自动化系, 济南 250000;²沈阳航空航天大学自动化学院, 沈阳 110000

基金项目: 山东省高等学校“青创科技计划”（2019KJN015）；山东省职业教育教学改革研究项目（2019301）

详细信息

作者简介:
张雅美（1991—），女，硕士(通讯作者. E-mail: amyzhang0203@126.com).

中图分类号: O231
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出版历程
- 收稿日期: 2020-01-13
- 修回日期: 2020-11-04
- 刊出日期: 2020-12-01

Finite-Time Function Projective Synchronization of Unknown Cohen-Grossberg Neural Networks With Time Delays and Stochastic Disturbances and Its Application in Secure Communication

¹Department of Electrical and Automation, Shandong Labor Vocational and Technical College, Jinan 250000, P.R.China;²School of Automation, Shenyang Aerospace University, Shenyang 110000, P.R.China

摘要

摘要: 针对具有时延和随机扰动的未知CG神经网络，研究了有限时间函数投影同步在保密通信中的应用问题.基于有限时间稳定性定理和Lyapunov稳定性理论，结合开环控制和反馈控制，提出了一种新的混合控制策略，实现了驱动响应复杂网络在有限时间内的函数投影同步，完成了未知参数的辨识，并给出了同步过渡时间上界的估计.仿真实验验证了所提方法的有效性以及在保密通信中应用的可行性.
- 同步 /
- C-G神经网络 /
- 有限时间 /
- 保密通信
Abstract: 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.
- synchronization /
- Cohen-Grossberg neural network /
- finite time /
- secure communication

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参考文献(21)

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