在一个异质的双神经元鲁尔科夫网络中具有极端的多稳定性和相位同步,具有记忆电磁感应
Quan Xu1, Tong Liu1, Shoukui Ding1
1School of Microelectronics and Control Engineering, Changzhou University, Changzhou, 213164 China.
Cognitive neurodynamics
|June 2, 2023
概括
这项研究探讨了异构的鲁尔科夫神经元网络中的记忆电磁感应效应. 研究人员发现了复杂的动态,包括极端的多稳定性和相同步,受到memristor属性和初始条件的影响.
科学领域:
- 计算神经科学是一种神经科学.
- 复杂的系统复杂的系统.
- 非线性动力学是一种非线性动力学.
背景情况:
- 记忆电磁感应效应在同质神经网络中得到了很好的研究.
- 对异质神经网络中这些效应的研究仍然有限.
- 将异质的鲁尔科夫神经元与记忆器结合在一起,为研究提供了一个新的途径.
研究的目的:
- 为了研究在合异质鲁尔科夫神经元网络中的记忆电磁感应效应.
- 分析网络平衡状态的稳定性及其对memristor参数的依赖性.
- 探索由memristor合产生的复杂的动态行为和同步现象.
主要方法:
- 理论分析直线平衡状态及其通过霍夫分叉的稳定性.
- 使用 Julia 和 MATLAB 的数值模拟来揭示动态行为.
- 使用基于MCU的硬件进行实验验证.
主要成果:
- 网络在不稳定的座焦点和稳定的节点焦点状态之间呈现过渡.
- 观察到不同的动态:点吸引器,周期,混乱,混乱危机和周期翻倍的分叉.
- 证明了极端的多稳定性和共存的多个发射模式,以及相位同步.
结论:
- 异质的双神经元鲁尔科夫网络与memristor合显示了丰富而复杂的动态.
- 记忆器合强度和初始条件显著影响网络行为和同步.
- 记忆器突触可塑性促进了神经网络中的适应性调节和能量平衡.
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