Novel Modeling of Memristive Cellular Neural Network and Its Circuit Simulation

Authors

Xiaohong Zhang, School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China;
Linyu Liao, School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China;
Lianghua Yu, School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China;

Abstract

Abstract: The memristor as the fourth fundamental circuit component included along with the resistor, capacitor and inductor could simulate the storage memory function of brain neural network. A traditional three-dimensional CNN was designed, and the output function was implemented with the nonlinear characteristics of a flux-controlled memristor. The conventional electronic devices in Multisim were utilized to simulate flux-controlled memristor which simplified the output function part of the circuits. To compare with the CNN system which has chaotic behaviors, the circuits of novel memristive cellular neural network not only can show a chaos attractors phenomenon, but also the inner magnetic energy of memristor is changed with state of CNN to achieve the equivalent values of output function. Numerical calculation and circuit simulation results verify its chaotic characteristics and feasibility, and can be applied in synchronization communication, image encryption and speech signal processing, et al.

Recommended Citation

Zhang, Xiaohong; Liao, Linyu; and Yu, Lianghua (2020) "Novel Modeling of Memristive Cellular Neural Network and Its Circuit Simulation," Journal of System Simulation: Vol. 28: Iss. 8, Article 2.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss8/2

First Page

1715

Revised Date

2015-05-03

DOI Link

https://doi.org/

Last Page

1725

CLC

TP391.9/O415.5

Recommended Citation

Zhang Xiaohong, Liao Linyu, Yu Lianghua. Novel Modeling of Memristive Cellular Neural Network and Its Circuit Simulation[J]. Journal of System Simulation, 2016, 28(8): 1715-1725.