主-奴隶同步异构维度比例延迟神经网络用于图像加密
1Department of Mathematics, Tianjin Normal University, Tianjin, 300387, China; Institute of Mathematics and Interdisciplinary Sciences, Tianjin Normal University, Tianjin, 300387, China.
概括
本研究探讨了具有比例时间延迟和不同维度的主-奴隶系统中的同步. 全球异常和指数同步的新标准是使用自适应观察者和控制器开发的.
科学领域:
- 控制系统工程 控制系统工程
- 计算神经科学是一种神经科学.
- 应用数学 应用数学 应用数学
背景情况:
- 主-奴隶同步对于协调系统至关重要.
- 现有研究往往假定相同的尺寸和有限的延迟,限制适用性.
- 相对延迟神经网络 (PDNNs) 由于时间变化的延迟而存在独特的挑战.
研究的目的:
- 在具有比例延迟和异质维度的主-奴隶系统中研究全球非对称同步 (GAS).
- 开发全球指数同步 (GES) 的标准,使用适应性观察员和控制器.
- 为了证明在图像加密中提出的同步方法的实际实用性.
主要方法:
- 减少级观察员和反控制器的设计.
- 在 GAS 分析中使用 Lyapunov-Krasovskii 函数式 (LKF).
- 观测器和控制器的优化,以适应性版本,用Lyapunov函数 (LF) 进行GES分析.
主要成果:
- 建立了一个全局非对称同步 (GAS) 的新标准.
- 全球指数同步 (GES) 的标准是通过自适应控制来得出的.
- 建议方法的有效性通过三个数值示例来验证.
结论:
- 开发的同步标准适用于具有比例延迟和异质尺寸的主-奴隶系统.
- 适应性观察器和控制器设计提高了系统的适应性,稳定性和性能.
- 同步技术对图像加密等应用非常有希望.
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