基于被动性和消散性的模糊控制,在时间尺度上对四次数值的记忆神经网络进行模糊控制
Ruoxia Li1, Jinde Cao2, Zhengwen Tu3
1School of Mathematics and Statistics, Shaanxi Normal University, Xi'an, 710062 China.
Cognitive neurodynamics
|July 3, 2025
概括
这项研究建立了分数顺序四次数值模糊记忆神经网络中被动性和消散性的新标准. 这些发现为分析这些复杂系统提供了有效的方法.
科学领域:
- 复杂系统分析 复杂系统分析
- 神经网络理论 神经网络理论
- 分数微积分的计算.
背景情况:
- 分数顺序系统提供了增强的建模功能.
- 记忆神经网络表现出复杂的动态.
- 四值系统对于先进的应用至关重要.
研究的目的:
- 研究分数顺序四次数值模糊记忆神经网络中的被动性和消散性.
- 为这些系统制定新的分析标准.
- 提供高效和可验证的分析方法.
主要方法:
- 构建一个合适的Lyapunov功能.
- 应用先进的不平等技术.
- 开发特定于四子的分析方法,避免大小考虑.
主要成果:
- 建立了改进的被动性标准.
- 推导出新的散射性结论.
- 通过标准数学计算来证明分析效率.
结论:
- 提出的技术有效地分析分数顺序四次数值的模糊记忆神经网络.
- 这些方法具有计算效率和可验证性.
- 模拟示例证实了开发的标准的有效性.
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