搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

非周期二进制/M进制信号激励下非线性系统的非周期共振研究

王重秋 杨建华

引用本文:
Citation:

非周期二进制/M进制信号激励下非线性系统的非周期共振研究

王重秋, 杨建华

Aperiodic resonance of a nonlinear system excited by aperiodic binary signal or M-ary signal

Wang Zhong-Qiu, Yang Jian-Hua
PDF
HTML
导出引用
  • 研究单一非周期二进制或M进制信号激励下一类非线性系统的非周期共振现象及其度量方法, 重点探讨了系统参数引起的非周期共振. 提出了适用于非周期共振度量的响应幅值增益指标, 并结合互相关系数和误码率展开研究. 结果发现, 互相关系数能够较好地描述系统输出和输入信号之间的同步性及波形相似性但无法刻画信号通过系统后被放大的程度. 响应幅值增益能够较好地描述信号通过系统后幅值被放大的程度, 但无法反映系统输出和输入信号之间的同步性及波形相似性. 非周期共振发生在互相关系数取谷值和响应幅值增益取峰值处, 且两种指标曲线反映的共振点相同. 误码率在合适的阈值下可以描述系统输出和输入信号之间的同步性以及非周期信号通过系统后被放大的程度, 误码率曲线可以直接给出非周期共振的共振区. 单一非周期二进制或M进制信号激励下的非线性系统可以发生非周期共振, 其共振效果需要综合互相关系数、响应幅值增益、误码率等指标进行度量.
    The aperiodic resonance of a typical nonlinear system that excited by a single aperiodic binary or M-ary signal and its measuring method are studied. The focus is on exploring aperiodic resonance caused by the system parameter. A response amplitude gain index suitable for aperiodic excitation is proposed to measure the effect of aperiodic resonance, and the research is carried out by combining the cross-correlation coefficient index and bit error rate index. The results show that the cross-correlation coefficient can better describe the synchronization and waveform similarity between the system output and the input aperiodic signal, but cannot describe the situation whether the signal is amplified after passing through the nonlinear system. The response amplitude gain can better describe the amplification of signal amplitude after passing through the nonlinear system, but cannot reflect the synchronization and waveform similarity between the system output and the input aperiodic signal. The aperiodic resonance occurs at the valley corresponding to the cross-correlation coefficient and the peak corresponding the response amplitude gain. The aperiodic resonance locations reflected on both the cross-correlation coefficient and the response amplitude gain curves are the same. The bit error rate can describe the synchronization between the system output and the input signal at appropriate thresholds, as well as the degree to which the aperiodic signal is amplified after passing through the nonlinear system. The bit error rate curve can directly indicate the resonance region of the aperiodic resonance. The aperiodic resonance can occur in a nonlinear system excited by a single aperiodic binary or M-ary signal, and its aperiodic resonance effect needs to be measured by combining the cross-correlation coefficient, response amplitude gain, bit error rate and other indices together.
      通信作者: 杨建华, jianhuayang@cumt.edu.cn
    • 基金项目: 国家自然科学基金(批准号:11672325, 12311530053)、江苏高校优势学科建设工程和江苏高校品牌建设工程资助的课题.
      Corresponding author: Yang Jian-Hua, jianhuayang@cumt.edu.cn
    • Funds: Project supported by the National Natural Science Foundation of China (Grant Nos. 11672325, 12311530053), the Priority Academic Program Development of Jiangsu Higher Education Institutions, China, and the Brand Construction Project of Jiangsu University, China.
    [1]

    Lee H, Lee I, Quek T Q, Lee S H 2018 Opt. Express 26 18131Google Scholar

    [2]

    Chizhevsky V N, Smeu E, Giacomelli G 2003 Phys. Rev. Lett. 91 220602Google Scholar

    [3]

    Chizhevsky V N, Giacomelli G 2008 Phys. Rev. E 77 051126Google Scholar

    [4]

    Liu J, Li Z 2015 IET Image Process. 9 1033Google Scholar

    [5]

    Chen W, Chen X 2015 Europhys. Lett. 110 44002Google Scholar

    [6]

    Gammaitoni L, Hänggi P, Jung P, Marchesoni F 1998 Rev. Mod. Phys. 70 223Google Scholar

    [7]

    Xu W, Jin Y F, Li W, Ma S J 2005 Chin. Phys. 14 1077Google Scholar

    [8]

    Jin Y F 2018 Chin. Phys. B 27 050501Google Scholar

    [9]

    靳艳飞, 许鹏飞, 李永歌, 马晋忠, 许勇 2023 力学进展 53 357Google Scholar

    Jin Y F, Xu P F, Li Y G, Ma J Z, Xu Y 2023 Advances in Mechanics 53 357Google Scholar

    [10]

    杨建华, 周登极 2020 变尺度共振理论及在故障诊断中的应用 (北京: 科学出版社)

    Yang J H, Zhou D J 2020 Re-scaled Resonance Theory and Applications in Fault Diagnosis (Beijing: Science Press

    [11]

    Landa P S, McClintock P V E 2000 J. Phys. A: Math. Gen. 33 L433Google Scholar

    [12]

    Rajasekar S, Miguel A F, Sanjuán 2016 Nonlinear Resonances (Switzerland: Springer International Publishing

    [13]

    Vincent U E, McClintock P V E, Khovanov I A, Rajasekar S 2021 Philos. T. R. Soc. A 379 20200226Google Scholar

    [14]

    Collins J J, Chow C C, Capela A C, Imhoff T T 1996 Phys. Rev. E 54 5575Google Scholar

    [15]

    Collins J J, Chow C C, Imhoff T T 1995 Phys. Rev. E 52 R3321Google Scholar

    [16]

    Heneghan C, Chow C C, Collins J J, Imhoff T T, Lowen S B, Teich M C 1996 Phys. Rev. E 54 R2228Google Scholar

    [17]

    Jia P X, Wu C J, Yang J H, Sanjuán M A F, Liu G X 2018 Nonlinear Dynam. 91 2699Google Scholar

    [18]

    杨建华, 马强, 吴呈锦, 刘后广 2018 物理学报 67 054501Google Scholar

    Yang J H, Ma Q, Wu C J, Liu H G 2018 Acta Phys. Sin. 67 054501Google Scholar

    [19]

    Duan L, Duan F, Chapeau-Blondeau F, Abbott D 2020 Phys. Lett. A 384 126143Google Scholar

    [20]

    Kang Y, Liu R, Mao X 2021 Cogn. Neurodynamics 15 517Google Scholar

    [21]

    Zhao J, Ma Y, Pan Z, Zhang H 2022 J. Syst. Sci. Complex. 35 179Google Scholar

    [22]

    Huang W, Zhang G, Jiao S, Wang J 2022 Appl. Sci. 12 12084Google Scholar

    [23]

    Zeng L, Li J, Shi J 2012 Chaos, Soliton. Fract. 45 378Google Scholar

    [24]

    Liang L, Zhang N, Huang H, Li Z 2019 China Commun. 16 196Google Scholar

    [25]

    McDonnell M D, Gao X 2015 Europhys. Lett. 108 60003Google Scholar

    [26]

    Cheng C, Zhou B, Gao X, McDonnell M D 2017 Physica A 479 48Google Scholar

    [27]

    Yang C, Yang J, Zhou D, Zhang S, Litak G 2021 Philos. T. R. Soc. A 379 20200239Google Scholar

    [28]

    Qin T, Zhou L, Chen S, Chen Z 2022 IEEE Sens. J. 22 17043Google Scholar

    [29]

    Xu Z, Wang Z, Yang J, Sanjuán M A F, Sun B, Huang S 2023 Eur. Phys. J. Plus 138 386Google Scholar

    [30]

    Chizhevsky V N 2014 Phys. Rev. E 89 062914Google Scholar

    [31]

    Morfu S, Usama B I, Marquié P 2019 Electron. Lett. 55 650Google Scholar

    [32]

    Morfu S, Usama B I, Marquié P 2021 Philos. T. R. Soc. A 379 20200240Google Scholar

    [33]

    Zhang S, Yang J, Zhang J, Liu H, Hu E 2019 Nonlinear Dynam. 98 2035Google Scholar

    [34]

    Zhai Y, Yang J, Zhang S, Liu H 2020 Phys. Scripta 95 065213Google Scholar

    [35]

    Yang J, Zhang S, Sanjuán M A F, Liu H 2020 Commun. Nonlinear Sci. Numer. Simulat. 85 105258Google Scholar

    [36]

    Jeevarathinam C, Rajasekar S, Sanjuán M A F 2011 Phys. Rev. E 83 066205Google Scholar

    [37]

    Li J L, Zeng L Z 2011 Chin. Phys. B 20 010503Google Scholar

  • 图 1  A = 0.3, T = 100时, 非周期二进制信号的不同时域波形. 自上而下信号分别标记为Signal 1, Signal 2, Signal 3

    Fig. 1.  Different waveforms of the aperiodic binary signal at A = 0.3, T = 100. The signals are labeled as Signal 1, Signal 2, Signal 3 from top to bottom.

    图 2  b = 2, A = 0.3, T = 100时, 不同波形的非周期二进制信号激励下, 系统输出与输入信号之间的互相关系数$ C_{sx} $与系统参数a之间的关系

    Fig. 2.  Cross-correlation coefficient $ C_{sx} $ between the system output and input signal versus the system parameter a under the excitation of aperiodic binary signal with different waveforms at b = 2, A = 0.3, T = 100.

    图 3  b = 2, A = 0.3, T = 100时, 系统参数a取值不同时输出的不同波形 (a) $ a=0 $; (b) $ a=1.05 $; (c) $ a=1.1 $; (d) $ a=2 $

    Fig. 3.  Different waveforms of the output under different values of the system parameter a with b = 2, A = 0.3, T = 100: (a) $ a=0 $; (b) $ a=1.05 $; (c) $ a=1.1 $; (d) $ a=2 $

    图 4  b = 2, A = 0.3, T = 100时, 响应幅值增益β与系统参数a之间的函数关系

    Fig. 4.  Response amplitude gain β versus the system parameter a with b = 2, A = 0.3, T = 100.

    图 5  b = 2, A = 0.3, T = 100时, 误码率BER与系统参数a之间的函数关系

    Fig. 5.  Bit error rate (BER) versus the system parameter a with b = 2, A = 0.3, T = 100

    图 6  M = 4, b = 2, A = 0.3, T = 100时, 非周期M进制信号的不同时域波形. 自上而下信号分别标记为Signal 4, Signal 5, Signal 6

    Fig. 6.  Different waveforms of the aperiodic M-ary signal with M = 4, b = 2, A = 0.3, T = 100. The signals are labeled as Signal 4, Signal 5, Signal 6 from top to bottom

    图 7  M = 4, b = 2, A = 0.3, T = 100时, 不同波形的非周期M进制信号激励下, 系统输出与输入信号之间的互相关系数$ C_{sx} $与系统参数a之间的关系

    Fig. 7.  Cross-correlation coefficient $ C_{sx} $ between the system output and input signal versus the system parameter a under the excitation of aperiodic M-ary signal with different waveforms at M = 4, b = 2, A = 0.3, T = 100.

    图 8  b = 2, A = 0.3, T = 100时, 系统参数a取值不同时输出的不同波形 (a) $ a=0 $; (b) $ a=2.2 $; (c) $ a=3 $; (d) $ a=5 $

    Fig. 8.  Different waveforms of the output under different values of the system parameter a with b = 2, A = 0.3, T = 100: (a) $ a=0 $; (b) $ a=2.2 $; (c) $ a=3 $; (d) $ a=5 $

    图 9  M = 4, b = 2, A = 0.3, T = 100时, 响应幅值增益β与系统参数a之间的函数关系

    Fig. 9.  Response amplitude gain β versus the system parameter a with M = 4, b = 2, A = 0.3, T = 100.

    图 10  M = 4, b = 2, A = 0.3, T = 100时, 误码率BER与系统参数a之间的函数关系

    Fig. 10.  Bit error rate BER versus the system parameter a with M = 4, b = 2, A = 0.3, T = 100

    图 11  M = 4, b = 2, A = 0.3, T = 100时, 系统参数a处于共振区时输出的波形 (a) $ a=0.65 $; (b) $ a=0.75 $; (c) $ a= 0.85 $; (d) $ a=0.95 $

    Fig. 11.  Different waveforms of the output when the system parameter a lies in the resonance region with M = 4, b = 2, A = 0.3, T = 100: (a) $ a=0.65 $; (b) $ a=0.75 $; (c) $ a=0.85 $; (d) $ a=0.95 $

  • [1]

    Lee H, Lee I, Quek T Q, Lee S H 2018 Opt. Express 26 18131Google Scholar

    [2]

    Chizhevsky V N, Smeu E, Giacomelli G 2003 Phys. Rev. Lett. 91 220602Google Scholar

    [3]

    Chizhevsky V N, Giacomelli G 2008 Phys. Rev. E 77 051126Google Scholar

    [4]

    Liu J, Li Z 2015 IET Image Process. 9 1033Google Scholar

    [5]

    Chen W, Chen X 2015 Europhys. Lett. 110 44002Google Scholar

    [6]

    Gammaitoni L, Hänggi P, Jung P, Marchesoni F 1998 Rev. Mod. Phys. 70 223Google Scholar

    [7]

    Xu W, Jin Y F, Li W, Ma S J 2005 Chin. Phys. 14 1077Google Scholar

    [8]

    Jin Y F 2018 Chin. Phys. B 27 050501Google Scholar

    [9]

    靳艳飞, 许鹏飞, 李永歌, 马晋忠, 许勇 2023 力学进展 53 357Google Scholar

    Jin Y F, Xu P F, Li Y G, Ma J Z, Xu Y 2023 Advances in Mechanics 53 357Google Scholar

    [10]

    杨建华, 周登极 2020 变尺度共振理论及在故障诊断中的应用 (北京: 科学出版社)

    Yang J H, Zhou D J 2020 Re-scaled Resonance Theory and Applications in Fault Diagnosis (Beijing: Science Press

    [11]

    Landa P S, McClintock P V E 2000 J. Phys. A: Math. Gen. 33 L433Google Scholar

    [12]

    Rajasekar S, Miguel A F, Sanjuán 2016 Nonlinear Resonances (Switzerland: Springer International Publishing

    [13]

    Vincent U E, McClintock P V E, Khovanov I A, Rajasekar S 2021 Philos. T. R. Soc. A 379 20200226Google Scholar

    [14]

    Collins J J, Chow C C, Capela A C, Imhoff T T 1996 Phys. Rev. E 54 5575Google Scholar

    [15]

    Collins J J, Chow C C, Imhoff T T 1995 Phys. Rev. E 52 R3321Google Scholar

    [16]

    Heneghan C, Chow C C, Collins J J, Imhoff T T, Lowen S B, Teich M C 1996 Phys. Rev. E 54 R2228Google Scholar

    [17]

    Jia P X, Wu C J, Yang J H, Sanjuán M A F, Liu G X 2018 Nonlinear Dynam. 91 2699Google Scholar

    [18]

    杨建华, 马强, 吴呈锦, 刘后广 2018 物理学报 67 054501Google Scholar

    Yang J H, Ma Q, Wu C J, Liu H G 2018 Acta Phys. Sin. 67 054501Google Scholar

    [19]

    Duan L, Duan F, Chapeau-Blondeau F, Abbott D 2020 Phys. Lett. A 384 126143Google Scholar

    [20]

    Kang Y, Liu R, Mao X 2021 Cogn. Neurodynamics 15 517Google Scholar

    [21]

    Zhao J, Ma Y, Pan Z, Zhang H 2022 J. Syst. Sci. Complex. 35 179Google Scholar

    [22]

    Huang W, Zhang G, Jiao S, Wang J 2022 Appl. Sci. 12 12084Google Scholar

    [23]

    Zeng L, Li J, Shi J 2012 Chaos, Soliton. Fract. 45 378Google Scholar

    [24]

    Liang L, Zhang N, Huang H, Li Z 2019 China Commun. 16 196Google Scholar

    [25]

    McDonnell M D, Gao X 2015 Europhys. Lett. 108 60003Google Scholar

    [26]

    Cheng C, Zhou B, Gao X, McDonnell M D 2017 Physica A 479 48Google Scholar

    [27]

    Yang C, Yang J, Zhou D, Zhang S, Litak G 2021 Philos. T. R. Soc. A 379 20200239Google Scholar

    [28]

    Qin T, Zhou L, Chen S, Chen Z 2022 IEEE Sens. J. 22 17043Google Scholar

    [29]

    Xu Z, Wang Z, Yang J, Sanjuán M A F, Sun B, Huang S 2023 Eur. Phys. J. Plus 138 386Google Scholar

    [30]

    Chizhevsky V N 2014 Phys. Rev. E 89 062914Google Scholar

    [31]

    Morfu S, Usama B I, Marquié P 2019 Electron. Lett. 55 650Google Scholar

    [32]

    Morfu S, Usama B I, Marquié P 2021 Philos. T. R. Soc. A 379 20200240Google Scholar

    [33]

    Zhang S, Yang J, Zhang J, Liu H, Hu E 2019 Nonlinear Dynam. 98 2035Google Scholar

    [34]

    Zhai Y, Yang J, Zhang S, Liu H 2020 Phys. Scripta 95 065213Google Scholar

    [35]

    Yang J, Zhang S, Sanjuán M A F, Liu H 2020 Commun. Nonlinear Sci. Numer. Simulat. 85 105258Google Scholar

    [36]

    Jeevarathinam C, Rajasekar S, Sanjuán M A F 2011 Phys. Rev. E 83 066205Google Scholar

    [37]

    Li J L, Zeng L Z 2011 Chin. Phys. B 20 010503Google Scholar

  • [1] 宫涛, 杨建华, 单振, 王志乐, 刘后广. 非线性调频信号激励下非线性系统的最优共振响应. 物理学报, 2022, 71(5): 050503. doi: 10.7498/aps.71.20211959
    [2] 张绿夷, 王革丽, 谭桂容, 吴越. 基于因果检验的非线性系统的预测试验. 物理学报, 2022, 71(8): 080502. doi: 10.7498/aps.71.20211871
    [3] 宫涛, 杨建华, 单振, 王志乐, 刘后广. NLFM信号激励下非线性系统的最优共振响应研究. 物理学报, 2021, (): . doi: 10.7498/aps.70.20211959
    [4] 张识, 王攀, 张瑞浩, 陈红. 选取任意庞加莱截面的新方法. 物理学报, 2020, 69(4): 040503. doi: 10.7498/aps.69.20191585
    [5] 潘昕浓, 王革丽, 杨培才. 利用慢特征分析法提取层次结构系统中的外强迫. 物理学报, 2017, 66(8): 080501. doi: 10.7498/aps.66.080501
    [6] 吴昊, 陈树新, 杨宾峰, 陈坤. 基于广义M估计的鲁棒容积卡尔曼滤波目标跟踪算法. 物理学报, 2015, 64(21): 218401. doi: 10.7498/aps.64.218401
    [7] 郭静波, 李佳文. 二进制信号的混沌压缩测量与重构. 物理学报, 2015, 64(19): 198401. doi: 10.7498/aps.64.198401
    [8] 杨志安. 非线性系统的非对角Berry相. 物理学报, 2013, 62(11): 110302. doi: 10.7498/aps.62.110302
    [9] 杨建华, 朱华. 不同周期信号激励下分数阶线性系统的响应特性分析. 物理学报, 2013, 62(2): 024501. doi: 10.7498/aps.62.024501
    [10] 杨芳艳, 胡明, 姚尚平. 连续时间系统同宿轨的搜索算法及其应用. 物理学报, 2013, 62(10): 100501. doi: 10.7498/aps.62.100501
    [11] 徐超, 康艳梅. 非高斯噪声激励下含周期信号FitzHugh-Nagumo系统的响应特征. 物理学报, 2011, 60(10): 108701. doi: 10.7498/aps.60.108701
    [12] 贾蒙, 樊养余, 李慧敏. 基于自适应因子轨道延拓法的不变流形计算. 物理学报, 2010, 59(11): 7686-7692. doi: 10.7498/aps.59.7686
    [13] 周颖, 臧强. 多输入多输出不确定非线性系统的输出反馈自适应机动控制. 物理学报, 2009, 58(11): 7565-7572. doi: 10.7498/aps.58.7565
    [14] 徐 云, 张建峡, 徐 霞, 周 红. Canard轨迹原理. 物理学报, 2008, 57(7): 4029-4033. doi: 10.7498/aps.57.4029
    [15] 秦卫阳, 苏 浩, 杨永峰. 利用Duffing系统的同步识别信号中的微小差别. 物理学报, 2008, 57(5): 2704-2707. doi: 10.7498/aps.57.2704
    [16] 周丙常, 徐 伟. 周期混合信号和噪声联合激励下的非对称双稳系统的随机共振. 物理学报, 2007, 56(10): 5623-5628. doi: 10.7498/aps.56.5623
    [17] 唐 晨, 闫海青, 张 皞, 刘 铭, 张桂敏. 任意阶隐式指数时程差分多步法及其在非线性系统中的应用. 物理学报, 2004, 53(6): 1699-1703. doi: 10.7498/aps.53.1699
    [18] 唐 晨, 张 皞, 闫海青, 张桂敏. 非线性系统的任意项精细积分外插多步法及其在混沌数值分析中的应用. 物理学报, 2003, 52(5): 1091-1095. doi: 10.7498/aps.52.1091
    [19] 张必达, 王卫东, 宋枭禹, 俎栋林, 吕红宇, 包尚联. 磁共振现代射频脉冲理论在非均匀场成像中的应用. 物理学报, 2003, 52(5): 1143-1150. doi: 10.7498/aps.52.1143
    [20] 冷永刚, 王太勇. 二次采样用于随机共振从强噪声中提取弱信号的数值研究. 物理学报, 2003, 52(10): 2432-2437. doi: 10.7498/aps.52.2432
计量
  • 文章访问数:  914
  • PDF下载量:  34
  • 被引次数: 0
出版历程
  • 收稿日期:  2023-07-17
  • 修回日期:  2023-08-11
  • 上网日期:  2023-09-12
  • 刊出日期:  2023-11-20

/

返回文章
返回