Generation of Neuromorphic Oscillators via Second-Order Memristive Circuits With Modified Chua Corsage Memristor

被引:0
|
作者
Song, Zhenyu [1 ]
Liu, Yue [2 ]
机构
[1] Jilin Technol Coll Elect Informat, Jilin 132021, Peoples R China
[2] Changchun Univ Technol, Coll Elect & Elect Engn, Changchun 130012, Peoples R China
关键词
Oscillators; Neuromorphics; Equivalent circuits; Memristors; Behavioral sciences; Fluctuations; Chaos; Parasitic capacitance; Chua corsage memristor; parasitic parameter; frequency response; small-signal equivalent circuit; neural oscillator;
D O I
10.1109/ACCESS.2023.3318117
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The study on neuromorphic oscillation behaviors and their oscillators have been considered as one of the most straightforward approaches to mimic some biological neurons via the configured nonlinear memristive equivalent circuits. Also, neuromorphic oscillation is one classical oscillation phenomenon, both the frequency response and zero-pole analysis could be clearly regarded as a complete description of the sinusoidal oscillation behavior for a nonlinear circuit. As one of the most classical memristors, Chua corsage memristor (CCM) is so famous to exhibit chaotic oscillation and neuromorphic dynamics due to its locally active and edge of chaos. However, the parasitic phenomena in the practical circuits are unique and tiny but existed as one of the inherent characteristics, which could lead to some unexpected results. Even a pretty small perturbation may heavily affect the quality of the entire system. In this paper, one modified CCM with the parasitic parameter (named g(p)) is proposed. Then, some unique and unusual phenomena are captured and analyzed. Moreover, the analysis on the distributions for the locally-active domains (LADs) and edge of chaos are presented. Furthermore, one small-signal equivalent circuit with a positive capacitance is introduced, as well as its impedance and admittance functions. Also, both types of neuromorphic oscillators are captured and observed via external inductor and capacitor, respectively. Finally, the applications in neural networks are explored, which herald the proposed model could be more suitable to transmit the mental, physical fatigue, memory load and closer to simulating the actual neuromorphic systems.
引用
收藏
页码:103712 / 103724
页数:13
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