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A strongly coupled oscillator can be used to detect weak pulse signals and recover waveforms, but its detection frequency of weak pulse signal is limited by the system’s built-in frequency. With a fixed built-in frequency, the system can only effectively detect and recover pulse signals in a certain frequency range, and waveform distortion occurs when pulse signals of higher frequencies are detected. In this work, the relationship between the built-in frequency of the coupled oscillator and the frequency detection range of weak pulse signal is analyzed, and two kinds of improved strongly coupled oscillator structures are proposed to extend the frequency detection range of weak pulse signals. By introducing the nonlinear restoring force coupling term, the nonlinear restoring force strongly coupled oscillator can effectively retain the high-frequency component of the signal, and can also better retain the signal characteristics when the pulse signal is input at a higher frequency. By introducing the Van der Pol-Duffing oscillator, the two-oscillator strong coupling system strengthens the stability of the internal structure of the system, and also achieves the effect of expanding the frequency detection range of the pulse signal. In addition, based on the variable iteration step size and frequency correlation of chaos detection, a method of detecting unknown frequency pulse signals is proposed. Instead of changing the built-in frequency of the system for frequency scanning, the method of changing the iteration step size is used. And using the frequency correlation of chaos detection, the correlation coefficient of the received signal and the recovered signal is compared with the correlation coefficient of the pure noise input case, then the pulse signals can be effectively detected based on the apparent difference between the two correlation coefficients. It is verified by simulation experiments that the proposed method can effectively detect the pulse signal of unknown frequency, and the proposed improved strong coupling oscillator has a greater performance improvement than that of the strong coupling oscillator.
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Keywords:
- strong coupling /
- nonlinear restoring force strongly coupled oscillator /
- two-oscillator strongly coupled system /
- weak pulse /
- transient pulse
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图 1 三角脉冲检测示意图 (a)原始三角脉冲及加噪三角脉冲; (b)系统恢复的三角脉冲波形; (c)系统两个振子的时域输出; (d)系统两个振子的相轨图
Figure 1. Triangular pulse detection diagram: (a) Original delta pulse and noise-added delta pulse; (b) delta pulse waveform after system recovery; (c) time domain output of two oscillators of the system; (d) phase track diagram of two oscillators of the system.
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[1] Su L Y 2010 Comput. Math. Appl. 59 737
Google Scholar
[2] 路鹏, 李月 2005 电子学报 33 527
Google Scholar
Lu P, Li Y 2005 Acta Electron. Sin. 33 527
Google Scholar
[3] Su L Y, Ma Y J, Li J J 2012 Chin. Phys. B 21 020508
Google Scholar
[4] Li M P, Xu X M, Yang B C, Ding J F 2015 Chin. Phys. B 24 060504
Google Scholar
[5] 王丹, 李安艺, 杨艳娟 2019 计算机应用 39 2652
Google Scholar
Wang D, Li A Y, Yang Y J 2019 J. Comput. Appl. 39 2652
Google Scholar
[6] 刘青, 常丁戈, 邓军波 2020 电工技术学报 35 3551
Google Scholar
Liu Q, Chang D G, Deng J B 2020 Trans. China Electrotechn. Soc. 35 3551
Google Scholar
[7] 刘欣宇, 杨苏辉, 廖英琦, 林学彤 2021 70 184205
Google Scholar
Liu X Y, Yang S H, Liao Y Q, Lin X T 2021 Acta Phys. Sin. 70 184205
Google Scholar
[8] 韩庆阳, 王晓东, 李丙玉, 周鹏骥 2015 电子与信息学报 37 1384
Google Scholar
Han Q Y, Wang X D, Li B Y, Zhou P G 2015 J. Electr. Inf. Technol. 37 1384
Google Scholar
[9] 赵雄文, 郭春霞, 李景春 2016 电子与信息学报 38 674
Google Scholar
Zhao X W, Guo C X, Li J C 2016 J. Electr. Inf. Technol. 38 674
Google Scholar
[10] 王永生, 姜文志, 赵建军, 范洪达 2008 2053
Google Scholar
Wang Y S, Jiang W Z, Zhao J J, Fan H D 2008 Acta Phys. Sin. 2053
Google Scholar
[11] 苏理云, 孙唤唤, 王杰, 阳黎明 2017 64 090503
Google Scholar
Su L Y, Sun H H, Wang J, Yang L M 2017 Acta Phys. Sin. 64 090503
Google Scholar
[12] 苏理云, 孙唤唤, 李晨龙 2017 电子学报 45 837
Google Scholar
Su L Y, Sun H H, Li C L 2017 Acta Electron. Sin. 45 837
Google Scholar
[13] 王慧武, 丛超 2016 电子学报 44 1450
Google Scholar
Wang H W, Cong C 2016 Acta Electron. Sin. 44 1450
Google Scholar
[14] Birx D L, Pipenberg S J 1992 International Joint Conference on Neural Networks (Vol. 2) Baltimore, USA, June 07–11, 1992 p881
[15] Yuan Y, Li Y, Mandic D P, Yang B J 2009 Chin. Phys. B 18 958
Google Scholar
[16] 吴勇峰, 张世平, 孙金玮, Peter Rolfe 2011 60 020511
Google Scholar
Wu Y F, Zhang S P, Sun J W, Rolfe P 2011 Acta Phys. Sin. 60 020511
Google Scholar
[17] 曾喆昭, 周勇, 胡凯 2015 64 070505
Google Scholar
Zeng Z Z, Zhou Y, Hu K 2015 Acta Phys. Sin. 64 070505
Google Scholar
[18] 张悦, 刘尚合, 胡小锋, 樊高辉 2016 高电压技术 42 2009
Google Scholar
Zhang Y, Liu S H, Hu X F, Fan G H 2016 High Voltage Eng. 42 2009
Google Scholar
[19] 曹保锋, 李鹏, 李小强, 张雪芹, 宁王师, 梁睿, 李欣, 胡淼, 郑毅 2019 68 080501
Google Scholar
Cao B F, Li P, Li X Q, Zhang X Q, Ning W S, Liang R, Li X, Hu M, Zheng Y 2019 Acta Phys. Sin. 68 080501
Google Scholar
[20] Luo W, Cui Y L 2020 IEEE Access 8 86554
Google Scholar
[21] Li G H, Hou Y M, Yang H 2022 Alex. Eng. J. 61 2859
Google Scholar
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