分数顺序的memristor-coupled tabu学习神经元模型的多稳定性和同步性
Dawei Ding1, Siqi Chen1, Zongli Yang1
1School of Electronics and Information Engineering, Anhui University, Hefei, 230601 China.
Cognitive neurodynamics
|June 30, 2025
概括
这项研究介绍了一种分数顺序的memristor模型,其中有两个tabu学习神经元,展示了复杂的行为和可控制的同步. 该研究使用微控制器实现验证发现.
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
- 非线性动力学是一种非线性动力学.
背景情况:
- 基于memristor的神经网络提供复杂的动态.
- 分数顺序系统表现出丰富的行为.
- 了解多稳定性和同步性对于神经计算至关重要.
研究的目的:
- 提出和分析一个分数顺序的memristor-coupled同质模型与两个禁忌学习神经元.
- 研究复杂的共存行为,多稳定性和同步现象.
- 为灵活的同步设计控制算法,并通过硬件实现验证模型.
主要方法:
- 分数式微积分和记忆器电路理论.
- 两叉分析,利亚普诺夫指数和局部吸引盆地分析.
- 规范化平均同步错误计算和滑动模式控制算法设计.
主要成果:
- 拟议的模型表现出复杂的共存动态和多稳定性.
- 通过调整合强度和初始条件来实现全同步和相位同步的灵活控制.
- 滑动模式控制算法有效地同步了系统.
结论:
- 分数顺序的memristor合模型成功地展示了复杂的动态和可控制的同步.
- 这些发现有助于理解记忆神经网络及其应用.
- 硬件实现验证了理论和模拟结果.
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