预设时间融合 模糊零化神经网络用于混乱系统同步:FPGA验证和安全通信应用程序
Liang Xiao1,2, Lv Zhao3, Jie Jin1,3
1Sanya Institute of Hunan University of Science and Technology, Sanya 572024, China.
Sensors (Basel, Switzerland)
|September 13, 2025
概括
这项研究引入了一种新的预设时间模糊归零神经网络 (PTCFZNN),用于传感器网络中的混乱同步. 该模型确保可靠的混乱同步,增强数据安全性和在具有挑战性的环境中的通信.
科学领域:
- 非线性动力学和控制系统
- 计算智能和神经网络
- 安全的通信系统安全的通信系统
背景情况:
- 混乱系统对初始条件和复杂动态具有高度敏感性,这限制了它们的实际应用.
- 混乱系统的同步对于安全的数据传输至关重要,特别是在传感器网络中.
- 非周期性参数激发对控制混乱系统构成重大挑战.
研究的目的:
- 提出一种新的预设时间模糊零化神经网络 (PTCFZNN) 模型,以实现混乱的同步.
- 解决混乱系统中非周期性参数激发的复杂性.
- 验证拟议模型的实际可行性和应用价值.
主要方法:
- 开发一个基于Takagi-Sugeno模糊控制的PTCFZNN模型.
- 神经网络的设计,以处理混乱系统中复杂的动态变化.
- 使用现场可编程门阵列 (FPGA) 实验实现和验证.
主要成果:
- 在非周期性参数激发混乱系统中成功实现混乱同步.
- 通过FPGA实验验证硬件验证证实了该模型的实际工程可行性.
- 在混沌掩盖通信,增强机密性和防干扰能力方面表现出有效性.
结论:
- PTCFZNN模型有效地实现了非周期性参数激发系统的混乱同步.
- FPGA实现验证了模型适用于现实世界工程应用的适用性.
- 该模型为通过混沌掩盖通信保护传感器数据传输提供了显著的价值.
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