在随机网络攻击下,通过适应性事件触发神经网络的同步,并应用于Chua的电路
Yao Xu1, Chunyu Yang1, Linna Zhou1
1School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China; Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, Xuzhou, 221116, China.
概括
本研究介绍了针对网络攻击的神经网络 (NN) 的适应性事件触发控制. 它使用新的Lyapunov-Krasovskii功能 (LKF) 方法确保了系统的稳定性和性能.
科学领域:
- 控制系统工程 控制系统工程
- 网络安全 网络安全
- 计算神经科学是一种神经科学.
背景情况:
- 神经网络 (NN) 容易受到随机网络攻击,从而损害系统完整性.
- 现有的控制策略在资源利用和对复杂攻击的强度方面经常面临挑战.
研究的目的:
- 开发适应性事件触发方案 (AETS) 以在网络攻击下对NN进行强有力的同步控制.
- 提高网络资源效率和系统性能,防止欺骗和累积的动态网络攻击.
主要方法:
- 输出反控制器是使用适应事件触发方案 (AETS) 设计的.
- 同步问题被重新阐述为同步错误系统的稳定性分析.
- 采用定制的利亚普诺夫-克拉索夫斯基函数 (LKF) 来保证在H∞性能下对称稳定性.
主要成果:
- 拟议的AETS有效地提高了网络资源利用率.
- 设计的控制器确保了同步错误系统的非对称稳定性.
- 包括楚亚电路在内的模拟结果验证了控制器的可行性和通用性.
结论:
- 开发的自适应事件触发输出反控制是有效的同步神经网络在随机网络攻击.
- 该方法提供了一个强大的解决方案,用于提高网络神经系统的安全性和性能.
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