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Tong, Yu-Han; Ling, Guang; Guan, Zhi-Hong; Fan, Qingju; Wan, Li

Refined composite multiscale phase Rényi dispersion entropy for complexity measure. (English) Zbl 1539.94017

Int. J. Bifurcation Chaos Appl. Sci. Eng. 33, No. 5, Article ID 2350054, 15 p. (2023).

MSC:

94A17 Measures of information, entropy

Keywords:

complexity assessment; dispersion entropy; nonlinear time series; multiscale phase Rényi entropy; bearing fault diagnosis
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Full Text: DOI

References:

[1] Ahmed, M. U. & Mandic, D. P. [2011] “ Multivariate multiscale entropy: A tool for complexity analysis of multichannel data,” Phys. Rev. E84, 061918.
[2] Amadi, P. O., Ikot, A. N., Okorie, U. S.et al. [2022] “ Shannon entropy and complexity measures for Bohr Hamiltonian with triaxial nuclei,” Results Phys.39, 105744.
[3] Azami, H., Rostaghi, M., Abásolo, D. & Escudero, J. [2017] “ Refined composite multiscale dispersion entropy and its application to biomedical signals,” IEEE Trans. Biomed. Eng.64, 2872-2879.
[4] Bandt, C. & Pompe, B. [2002] “ Permutation entropy: A natural complexity measure for time series,” Phys. Rev. Lett.88, 174102.
[5] Barnett, L., Barrett, A. B. & Seth, A. K. [2009] “ Granger causality and transfer entropy are equivalent for Gaussian variables,” Phys. Rev. Lett.103, 238701.
[6] Borin, A. M. S. Jr, Humeau-Heurtier, A., Murta, L. O. Jr & Silva, L. E. V. [2021] “ Multiscale entropy analysis of short signals: The robustness of fuzzy entropy-based variants,” Entropy23, 1620-1634.
[7] Case Western Reserve University [2004-2015] “Bearing data center — seeded fault test data,” https://csegroups.case.edu/bearingdatacenter/home.
[8] Chakraborty, M. & Mitra, D. [2022] “ Automated detection of epileptic seizures using multiscale and refined composite multiscale dispersion entropy,” Chaos Solit. Fract.146, 110939.
[9] Chao, L. & Shang, P. [2019] “ Multiscale Tsallis permutation entropy analysis for complex physiological time series,” Physica A523, 10-20.
[10] Chen, W., Wang, Z., Xie, H. & Yu, W. [2007] “ Characterization of surface EMG signal based on fuzzy entropy,” IEEE Trans. Neural Syst. Rehabil. Eng.15, 266-272.
[11] Costa, M., Goldberger, A. L. & Peng, C. K. [2002] “ Multiscale entropy analysis of physiologic time series,” Phys. Rev. Lett.89, 068102.
[12] Deka, B. & Dipen, D. [2022] “ An improved multiscale distribution entropy for analyzing complexity of real-world signals,” Chaos Solit. Fract.158, 112101.
[13] Dong, W., Zhang, S., Jiang, A., Jiang, W., Zhang, L. & Hu, M. [2021] “ Intelligent fault diagnosis of rolling bearings based on refined composite multi-scale dispersion q-complexity and adaptive whale algorithm-extreme learning machine,” Measurement176, 108977.
[14] Fan, Q., Liu, S. & Wang, K. [2019] “ Multiscale multifractal detrended fluctuation analysis of multivariate time series,” Physica A532, 121864.
[15] Gao, S., Ren, Y., Zhang, Y. & Li, T. [2022] “ Fault diagnosis of rolling bearings based on improved energy entropy and fault location of triangulation of amplitude attenuation outer raceway,” Measurement185, 109974.
[16] Gong, Y., Li, X., Cong, X. & Liu, H. [2020] “ Research on the complexity of forms and structures of urban green spaces based on fractal models,” Complexity2020, 4213412.
[17] Gu, D., Mi, Y. & Lin, A. [2021] “ Application of time-delay multiscale symbolic phase compensated transfer entropy in analyzing cyclic alternating pattern (CAP) in sleep-related pathological data,” Commun. Nonlin. Sci. Numer. Simul.99, 105835. · Zbl 1464.94016
[18] Hua, S., Shi, Y. & Hao, Z. [2018] “ Lyapunov exponents, sensitivity, and stability for non-autonomous discrete systems,” Int. J. Bifurcation and Chaos28, 1850088-1-7. · Zbl 1392.37025
[19] Humeau-Heurtier, A. [2015] “ The multiscale entropy algorithm and its variants: A review,” Entropy17, 3110-3123.
[20] Jiang, W., Xu, Y., Chen, Z., Zhang, N. & Zhou, J. [2022] “ Fault diagnosis for rolling bearing using a hybrid hierarchical method based on scale-variable dispersion entropy and parametric t-SNE algorithm,” Measurement191, 110843.
[21] Kang, H., Zhang, X. & Zhang, G. [2021] “ Phase permutation entropy: A complexity measure for nonlinear time series incorporating phase information,” Physica A568, 125686. · Zbl 07457008
[22] Kosko, B. [1986] “ Fuzzy entropy and conditioning,” Inf. Sci.40, 165-174. · Zbl 0623.94005
[23] Lacasa, L. & Just, W. [2017] “ Visibility graphs and symbolic dynamics,” Physica D374, 35-44. · Zbl 1392.37012
[24] Li, C., Zheng, J., Pan, H., Tong, J. & Zhang, Y. [2019] “ Refined composite multivariate multiscale dispersion entropy and its application to fault diagnosis of rolling bearing,” IEEE Access7, 47663-47673.
[25] Li, C. B. & Ye, Y. L. [2023] “ A comparison of topological entropies for nonautonomous dynamical systems,” J. Math. Anal. Appl.517, 126627. · Zbl 1505.37029
[26] Ling, G., Guan, Z.-H., Chen, J. & Lai, Q. [2019] “ Chaotifying stable linear complex networks via single pinning impulsive strategy,” Int. J. Bifurcation and Chaos29, 1950024-1-9. · Zbl 1414.34048
[27] Lobier, M., Siebenhuhner, F., Palva, S. & Palva, J. M. [2014] “ Phase transfer entropy: A novel phase-based measure for directed connectivity in networks coupled by oscillatory interactions,” Neuroimage85, 853-872.
[28] Ma, L., Liu, X., Liu, X., Zhang, Y., Qin, Y. & Li, K. [2020] “ On the correlation dimension of discrete fractional chaotic systems,” Int. J. Bifurcation and Chaos30, 2050174-1-14. · Zbl 1452.37080
[29] Ng, B. S. W., Logothetis, N. K. & Kayser, C. [2013] “ EEG phase patterns reflect the selectivity of neural firing,” Cereb. Cortex23, 389-398.
[30] Nieto-del-Amor, F., Beskhani, R., Ye-Lin, Y.et al. [2021] “ Assessment of dispersion and bubble entropy measures for enhancing preterm birth prediction based on electrohysterographic signals,” Sensors21, 6071-6087.
[31] Oppenheim, A. V. & Lim, J. S. [1981] “ The importance of phase in signals,” P. IEEE69, 529-541.
[32] Pincus, S. M. [1991] “ Approximate entropy as a measure of system complexity,” Proc. Natl. Acad. Sci.88, 2297-2301. · Zbl 0756.60103
[33] Qin, G. & Shang, P. [2021] “ Analysis of time series based on a new entropy plane by using weighted dispersion pattern,” Int. J. Bifurcation and Chaos31, 2150128-1-26. · Zbl 1471.62474
[34] Ramdani, S., Seigle, B., Lagarde, J., Bouchara, F. & Bernard, P. L. [2009] “ On the use of sample entropy to analyze human postural sway data,” Med. Eng. Phys.31, 1023-1031.
[35] Restrepo, J. F., Mateos, D. M. & Schlotthauer, G. [2020] “ Transfer entropy rate through lempel-ziv complexity,” Phys. Rev. E101, 052117.
[36] Rostaghi, M. & Azami, H. [2016] “ Dispersion entropy: A measure for time-series analysis,” IEEE Sign. Proc. Lett.23, 610-614.
[37] Rostaghi, M., Khatibi, M. M., Ashory, M. R. & Azami, H. [2021] “ Bearing fault diagnosis using refined composite generalized multiscale dispersion entropy-based skewness and variance and multiclass FCM-ANFIS,” Entropy23, 1510-1526.
[38] Schreiber, T. [2000] “ Measuring information transfer,” Phys. Rev. Lett.85, 461-464.
[39] Shang, D. & Shang, P. [2020] “ The Fisher-DisEn plane: A novel approach to distinguish different complex systems,” Commun. Nonlin. Sci.89, 105271. · Zbl 1451.91190
[40] Sinha, K. & Weck, O. [2016] “ Empirical validation of structural complexity metric and complexity management for engineering systems,” Syst. Eng.19, 193-206.
[41] Song, E., Ke, Y., Yao, C., Dong, Q. & Yang, L. [2019] “ Fault diagnosis method for high-pressure common rail injector based on IFOA-VMD and hierarchical dispersion entropy,” Entropy21, 923-942.
[42] Suguro, T. [2022] “ Shannon’s inequality for the Rényi entropy and an application to the uncertainty principle,” J. Funct. Anal.283, 109566. · Zbl 1492.94044
[43] Tan, H., Xie, S., Liu, R. & Ma, W. [2021] “ Bearing fault identification based on stacking modified composite multiscale dispersion entropy and optimised support vector machine,” Measurement186, 110180.
[44] Wan, L., Ling, G., Guan, Z.-H.et al. [2022] “ Fractional multiscale phase permutation entropy for quantifying the complexity of nonlinear time series,” Physica A600, 127506. · Zbl 07543437
[45] Wang, Z. & Shang, P. [2021] “ Generalized entropy plane based on multiscale weighted multivariate dispersion entropy for financial time series,” Chaos Solit. Fract.142, 110473.
[46] Wang, Z., Lin, T., Yao, L. & Zhang, J. [2021] “ A novel data-driven fault diagnosis method based on VMD-RCMFE-DDMA-BASSVM model for rolling bearings,” ICSP Proc.6, 171-176.
[47] Wang, Y., Xu, Y., Liu, M., Guo, Y., Wu, Y., Chen, C. & Chen, W. [2022a] “ Cumulative residual symbolic dispersion entropy and its multiscale version: Methodology, verification, and application,” Chaos Solit. Fract.160, 112266.
[48] Wang, Z., Yang, J. & Guo, Y. [2022b] “ Unknown fault feature extraction of rolling bearings under variable speed conditions based on statistical complexity measures,” Mech. Syst. Sign. Process.172, 108964.
[49] Wu, C., Zhang, Q., Yang, N., Jia, R. & Liu, C. [2022] “ Dynamical Analysis of a fractional-order boost converter with fractional-order memristive load,” Int. J. Bifurcation and Chaos32, 2250032-1-14. · Zbl 1494.34126
[50] Xia, J., Shang, P., Wang, J. & Shi, W. [2014] “ Classifying of financial time series based on multiscale entropy and multiscale time irreversibility,” Physica A400, 151-158.
[51] Xu, M., Shang, P. & Zhang, S. [2021] “ Complexity analysis of the time series using inverse dispersion entropy,” Nonlin. Dyn.105, 499-514.
[52] Yadav, G. S., Guha, A. & Chakrabarti, A. S. [2020] “ Measuring complexity in financial data,” Front. Phys.8, 0339.
[53] Zanin, M., Zunino, L., Rosso, O. A. & Papo, D. [2012] “ Permutation entropy and its main biomedical and econophysics applications: A review,” Entropy14, 1553-1577. · Zbl 1314.94033
[54] Zhang, X., Zhao, J., Teng, H. & Liu, G. [2019] “ A novel faults detection method for rolling bearing based on RCMDE and ISVM,” J. Vibroeng.21, 2148-2158.
[55] Zhang, X., Zhang, M., Wan, S., He, Y. & Wang, X. [2021] “ A bearing fault diagnosis method based on multiscale dispersion entropy and GG clustering,” Measurement185, 110023.
[56] Zheng, J., Pan, H. & Cheng, J. [2017] “ Rolling bearing fault detection and diagnosis based on composite multiscale fuzzy entropy and ensemble support vector machines,” Mech. Syst. Sign. Process.85, 746-759.
[57] Zheng, J., Pan, H., Tong, J. & Liu, Q. [2022] “ Generalized refined composite multiscale fuzzy entropy and multi-cluster feature selection based intelligent fault diagnosis of rolling bearing,” ISA Trans.123, 136-151.
[58] Zhou, Q. & Shang, P. [2020] “ Weighted multiscale cumulative residual Rényi permutation entropy of financial time series,” Physica A540, 123089.
[59] Zhou, Y., Lu, J., Hu, Z., Dong, H., Yan, W. & Yang, D. [2022] “ Novel feature extraction method of pipeline signals based on multi-scale dispersion entropy partial mean of multi-modal component,” Measurement205, 112137.
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