模糊合反应-扩散神经网络的被动性和同步性
IEEE transactions on cybernetics
|September 3, 2025
概括
本研究引入了适应性控制方法,以确保模糊合反应扩散神经网络 (FCRDNNs) 的被动性和同步性. 这些技术已被验证为具有多状态或空间扩散合的网络.
科学领域:
- 控制理论
- 人工神经网络
- 非线性动力学
背景情况:
- 模糊合反应扩散神经网络 (FCRDNNs) 是复杂的系统,需要强大的控制策略.
- 确保网络的被动性和同步性对于网络的稳定性和可靠性至关重要.
- 现有的方法可能无法完全解决多状态或空间扩散合所带来的挑战.
研究的目的:
- 开发和验证适应性控制方案,以实现FCRDNN的被动性和同步性.
- 研究多态和空间扩散合的FCRDNN的被动性和同步性.
- 为拟议的控制策略提供理论标准和实际验证.
主要方法:
- 适应状态反控制用于设计控制器.
- 使用Lyapunov功能方法分析系统稳定性并推导控制条件.
- 消极性标准和同步条件是用数学形式制定的.
- 进行数值模拟以证明拟议方法的有效性.
主要成果:
- 对于使用自适应状态反控制的多状态合器的FCRDNN,可以推导出几种被动性标准.
- 建立一个足够的条件来保证多状态合的FCRDNN的同步.
- 适应性控制技术和Lyapunov功能方法成功地解决了空间扩散合的FCRDNN的被动性和同步性.
- 数字示例证实了开发的适应性控制方案的有效性.
结论:
- 拟议的自适应控制方案有效地实现了各种合结构的FCRDNN的被动性和同步.
- 这项研究为控制复杂神经网络动态提供了理论框架和实践验证.
- 这些发现有助于推进分布式参数系统的可靠控制策略.
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