具有和没有冲动效应的多重量分数顺序合神经网络的有限时间集群同步
1School of Mathematical Sciences, Key Laboratory of Intelligent Computing and Applications (Ministry of Education), Tongji University, Shanghai 200092, China.
概括
本研究介绍了为多重量分数顺序神经网络的有限时间集群同步 (FTCS). 新的控制器确保同步,即使有混合的冲动效应,通过模拟验证.
科学领域:
- 计算神经科学是一种神经科学.
- 混沌理论 混沌理论
- 分数微积分的计算.
背景情况:
- 神经网络是复杂的动态系统,在各种领域都有应用.
- 神经网络中的同步现象对于理解它们的集体行为至关重要.
- 分数式微积分为建模动态系统提供了更普遍的方法.
研究的目的:
- 在多重权分序神经网络中研究有限时间集群同步 (FTCS).
- 开发新的控制策略,以在不同的网络条件下实现FTCS.
- 建立FTCS的理论标准,特别是解决混合冲动效应.
主要方法:
- 设计一个新的延迟状态反控制器来实现FTCS.
- 构建一个新的零件式控制器来处理混合的同步和非同步冲动.
- 利用分数计算和利亚普诺夫稳定性理论进行理论分析.
主要成果:
- 在多重权分序神经网络中实现有限时间集群同步的新标准得到了推导.
- 拟议的控制器有效地确保FTCS,即使在混合冲动效应的存在.
- 数字模拟证实了理论结果的有效性和有效性.
结论:
- 这项研究是对多重权重神经网络有限时间集群同步的首次调查.
- 开发的控制方法为实现复杂的分数顺序神经系统中的同步提供了强大的框架.
- 这些发现有助于理论理解和分数级神经网络的实际控制.
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