A memristive chaotic system and its application in weak signal detection

被引:6
作者
Yan, Shaohui [1 ,2 ]
Song, Jincai [1 ]
Cui, Yu [1 ]
Li, Lin [1 ]
Wang, Jianjian [1 ]
机构
[1] Northwest Normal Univ, Coll Phys & Elect Engn, Lanzhou 730070, Peoples R China
[2] Engn Res Ctr Gansu Prov Intelligent Informat Techn, Lanzhou 730070, Gansu, Peoples R China
关键词
chaotic system; memristor; circuit simulation; backstepping synchronization; weak signal detection; DUFFING OSCILLATOR; CIRCUIT IMPLEMENTATION;
D O I
10.1088/1402-4896/acf5af
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
In this paper, a novel four-dimensional memristive chaotic system is constructed by incorporating a memristor model into a three-dimensional chaotic system. Through the analysis of the Lyapunov exponent, bifurcation diagram, and Poincare cross-section of the system, it has been observed that the system is capable of exhibiting a stable chaotic state, as well as complex dynamic behaviors, such as attractor coexistence, transient chaos, and offset boosting. To validate the actual existence of the system, a real circuit has been built based on Multisim simulation, and the numerical simulation results, along with the actual simulation results, are in agreement, thereby confirming the practical feasibility of the circuit. To achieve weak signal detection, a backstepping synchronization controller has been designed, which can detect the frequency and amplitude of unknown signals. It is obvious that this method does not require the determination of the critical threshold. Instead of, it relies on the system being in a chaotic state. The proposed detection method provides a new perspective for weak signal detection.
引用
收藏
页数:17
相关论文
共 47 条
[1]  
Adiyaman Y., 2020, Chaos Theory Appl., V2, P10
[2]   A novel chaos based optical image encryption using fractional Fourier transform and DNA sequence operation [J].
Ben Farah, M. A. ;
Guesmi, R. ;
Kachouri, A. ;
Samet, M. .
OPTICS AND LASER TECHNOLOGY, 2020, 121
[3]  
Birx D. L., 1992, IJCNN International Joint Conference on Neural Networks (Cat. No.92CH3114-6), P881, DOI 10.1109/IJCNN.1992.226876
[4]   Classification of chaotic time series with deep learning [J].
Boulle, Nicolas ;
Dallas, Vassilios ;
Nakatsukasa, Yuji ;
Samaddar, D. .
PHYSICA D-NONLINEAR PHENOMENA, 2020, 403
[5]   The Fourth Element [J].
Chua, Leon O. .
PROCEEDINGS OF THE IEEE, 2012, 100 (06) :1920-1927
[6]   MEMRISTOR - MISSING CIRCUIT ELEMENT [J].
CHUA, LO .
IEEE TRANSACTIONS ON CIRCUIT THEORY, 1971, CT18 (05) :507-+
[7]   Determining the chaotic behaviour of copper prices in the long-term using annual price data [J].
Tapia Cortez C.A. ;
Coulton J. ;
Sammut C. ;
Saydam S. .
Palgrave Communications, 4 (1)
[8]   Chaotic Secure Communication Based on Single Feedback Phase Modulation and Channel Transmission [J].
Cui, Shuangyi ;
Zhang, Jianzhong .
IEEE PHOTONICS JOURNAL, 2019, 11 (05)
[9]   Hidden and Coexisting Attractors in a Novel 4D Hyperchaotic System with No Equilibrium Point [J].
Dong, Chengwei ;
Wang, Jiahui .
FRACTAL AND FRACTIONAL, 2022, 6 (06)
[10]   A coupling method of double memristors and analysis of extreme transient behavior [J].
Du, Chuanhong ;
Liu, Licai ;
Zhang, Zhengping ;
Yu, Shixing .
NONLINEAR DYNAMICS, 2021, 104 (01) :765-787