记忆电阻器
吸引子
物理
分段
脉搏(音乐)
混乱的
人工神经网络
激发
控制理论(社会学)
生物系统
拓扑(电路)
统计物理学
电压
计算机科学
数学分析
数学
人工智能
量子力学
控制(管理)
组合数学
生物
出处
期刊:Physics Letters A
日期:2024-10-01
卷期号:522: 129789-129789
标识
DOI:10.1016/j.physleta.2024.129789
摘要
This paper investigates the effect of pulsed currents and multi-piecewise memristor on dynamic behavior of memristive Hopfield neural network (HNN). Firstly, a four-neuron HNN model is constructed by using the traditional memristor as the connecting synapse and its dynamic behavior is analyzed. Secondly, the traditional memristor in the HNN is replaced with a multi-piecewise memristor, and external pulse currents are applied to the model. The system exhibits rich dynamical behavior by introducing varying numbers of pulse current stimuli and adjusting the parameters of the multi-piecewise memristor. Experimental results demonstrate that the number of attractors in the system changes when pulse currents are applied, and after a period of chaotic behavior, the system eventually exhibits periodic activity. Furthermore, adjusting the parameters of the multi-piecewise memristor can generate multiple scroll attractors in the system. Finally, the experimental results were verified by Multisim.
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