适应性事件触发的延迟外同步对于具有多状态或多衍生合的合神经网络
IEEE transactions on cybernetics
|March 3, 2025
概括
本研究介绍了多态合神经网络 (MSCCNN) 和多衍生合神经网络 (MDCCNN). 它建立了使用自适应事件触发控制在这些网络中延迟外部同步的标准,确保没有发生Zeno行为.
科学领域:
- 复杂的系统复杂的系统.
- 计算神经科学是一种神经科学.
- 控制理论 控制理论
背景情况:
- 结合的神经网络对于建模复杂系统至关重要.
- 实现这些网络的同步对于它们的可靠运行至关重要.
- 事件触发控制通过减少通信负载来提高效率.
研究的目的:
- 研究多态合神经网络 (MSCCNN) 和多衍生合神经网络 (MDCCNN) 中的延迟外部同步.
- 开发适应性事件触发控制方案,以实现和验证同步.
- 确保在拟议的控制策略中没有Zeno行为.
主要方法:
- 用基于节点的自适应事件触发控制来推导MSCCNN的延迟外部同步标准.
- 基于边缘的适应性事件触发控制用于MSCCNN同步的应用.
- 开发基于节点和边缘的适应性事件触发控制策略,用于MDCCNN同步.
- 数学证明Zeno行为不存在的证明.
主要成果:
- 成功导出了MSCCNN和MDCCNN的延迟外部同步标准.
- 基于节点和边缘的自适应事件触发控制方案的有效性.
- 证明拟议的控制方法可以防止Zeno行为.
- 通过两个说明性例子验证控制方案.
结论:
- 拟议的自适应事件触发控制方案有效地实现了MSCCNN和MDCCNN的延迟外部同步.
- 开发的方法是稳固的,并保证没有Zeno行为.
- 这些发现为复杂的合神经网络系统提供了实际的控制策略.
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