对于中性型SMJ神经网络的动态事件触发同步控制,在同步攻击下增加延迟
Zou Yang1, Jun Wang1, Kaibo Shi2
1College of Electrical and Information Engineering, Southwest Minzu University, Chengdu, 610041, P.R. China.
ISA transactions
|February 11, 2025
概括
这项研究引入了双动态事件触发机制,用于在攻击下同步半马科维亚跳跃神经网络. 这种方法节约了资源,并减少了计算负载,以提高网络性能.
科学领域:
- 控制理论 控制理论
- 网络化系统 网络化系统
- 计算神经科学是一种神经科学.
背景情况:
- 神经网络对于复杂的计算至关重要,但易受攻击.
- 事件触发机制 (ETM) 旨在减少通信和计算负载.
- 半马科维斯跳跃 (SMJ) 系统引入了复杂的动态,具有依赖状态的过渡概率.
研究的目的:
- 为中性型SMJ神经网络开发一个双动态事件触发同步 (DDETM) 策略.
- 模拟和减轻同步攻击对网络同步的影响.
- 通过先进的数学技术,减少同步标准的保守性.
主要方法:
- 模拟同步攻击使用一个独立的半马科维亚跳跃过程.
- 设计双动态事件触发机制 (DDETM) 以提高通信和计算效率.
- 纳入添加式变时延迟 (TVD) 来建模网络不确定性.
- 开发一个半马科夫动态事件触发控制器.
- 利用不对称的Lyapunov-Krasovskii函数 (LKFs) 和相互凸不等式 (RCCI) 来减少保守主义.
主要成果:
- 拟议的DDETM有效地节约了通信资源,并减少了计算负担.
- 设计的控制器在同步攻击下确保中性型SMJ神经网络的同步.
- 使用不对称的LKF和RCCI显著降低了同步标准的保守性.
- 模拟结果验证了拟议的同步方法的有效性.
结论:
- 开发的事件触发同步策略对中性型SMJ神经网络在同步攻击下有效.
- 提出的方法提供了一种实际的方法来提高网络神经系统的稳定性和效率.
- 这项研究有助于推进复杂动态系统的安全和有效的控制策略.
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