对于含有memristor的模糊多维值的NN进行多稳定性分析的一般方法
Yiming Zhao1, Song Zhu1, Junwei Sun2
1School of Mathematics, China University of Mining and Technology, Xuzhou, 221116, China.
概括
这项研究引入了一种新的方法来分析模糊的多维值记忆神经网络 (FMVMNNs) 具有时间变化的延迟. 新的标准确保了稳定的平衡点,改善了网络分析.
科学领域:
- 神经科学是一个神经科学.
- 复杂的系统复杂的系统.
- 计算智能是一种计算智能.
背景情况:
- 记忆神经网络对于复杂的计算至关重要.
- 分析具有不同时间延迟的系统存在重大挑战.
- 模糊逻辑集成增强了不确定的动态的建模.
研究的目的:
- 在模糊的多维值记忆神经网络 (FMVMNNs) 中开发多稳定性分析的通用分析方法.
- 建立足够的标准,以确定FMVMNNs中具有无限时间变化延迟的平衡点的存在和局部不对称稳定性.
- 为了估计这些复杂的神经网络中稳定的平衡的吸引力盆地.
主要方法:
- 状态空间分解与布劳威尔固定点定理相结合.
- 模糊逻辑原理与记忆神经网络动态的整合.
- 涵盖实数,复数和四次数系统的分析.
主要成果:
- 为存在多个平衡点 (EP) 推导出足够的标准.
- 确定了这些EP子集的局部非对称稳定性的条件.
- 开发了估计稳定平衡吸引力盆地的方法.
结论:
- 稳定性分析的拟议标准比现有方法更轻松,更容易验证.
- 一般化方法适用于各种数系 (实数,复数,四次数).
- 数字示例验证了理论发现和分析的有效性.
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