神经形态工程学
记忆电阻器
混乱的边缘
计算机科学
分叉
冯·诺依曼建筑
电容
GSM演进的增强数据速率
拓扑(电路)
电子工程
物理
控制理论(社会学)
人工神经网络
非线性系统
人工智能
工程类
电气工程
量子力学
操作系统
控制(管理)
电极
作者
Peipei Jin,Guangyi Wang,Yan Liang,Herbert Ho-Ching Iu,Leon O. Chua
出处
期刊:IEEE Transactions on Circuits and Systems I-regular Papers
[Institute of Electrical and Electronics Engineers]
日期:2021-11-01
卷期号:68 (11): 4419-4432
被引量:29
标识
DOI:10.1109/tcsi.2021.3121676
摘要
Neuromorphic computing can solve computationally hard problems with energy efficiencies unattainable for von Neumann architectures. A locally-active memristor, which possesses the capability to amplify infinitesimal fluctuations in energy and can be used to generate neuromorphic behaviors, is a natural candidate for constructing an electronic equivalent of biological neurons. This paper identifies some unknown neuromorphic dynamics of the Chua corsage memristor (CCM), and shows that the CCM, when biased at the edge of chaos domain, can exhibit rich dynamics of biological neurons. Using Chua’s theories of local activity and edge of chaos, we demonstrate that under the destabilizing of the input voltage and the circuit parameters (inductance or capacitance), two CCM-based circuits can produce thirteen types of neuromorphic behaviors either on, or near the edge of chaos domain via supercritical or subcritical Hopf bifurcation. In addition, we give the conditions to test the edge of chaos of the CCM and the CCM-based circuit only by using the poles and the zero of their admittance functions.
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