[1] Huang N E, Shen Z, Long S R, Wu M C, Shih H H, Zheng Q N, Yen N C, Tung C C, Liu H H. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society A:Mathematical, Physical and Engineering Sciences, 1998, 454(1971):903-995 doi: 10.1098/rspa.1998.0193
[2] Zhang H J, Bi G A, Razul S G, See C M S. Robust time-varying filtering and separation of some nonstationary signals in low SNR environmentsx. Signal Processing, 2015, 106:141-158 https://www.researchgate.net/publication/264980853_Robust_time-varying_filtering_and_separation_of_some_nonstationary_signals_in_low_SNR_environments
[3] Brigham E O. The Fast Fourier Transform and Its Applications. Englewood Cliffs, New Jersey, USA:Prentice Hall, 1988.
[4] Rai V K, Mohanty A R. Bearing fault diagnosis using FFT of intrinsic mode functions in Hilbert-Huang transform. Mechanical Systems and Signal Processing, 2007, 21(6):2607-2615 https://www.researchgate.net/publication/223040719_Bearing_fault_diagnosis_using_FFT_of_intrinsic_mode_functions_in_HilbertHuang_transform
[5] Feng Z P, Liang M, Chu F L. Recent advances in time-frequency analysis methods for machinery fault diagnosis:a review with application examples. Mechanical Systems and Signal Processing, 2013, 38(1):165-205 doi: 10.1016/j.ymssp.2013.01.017
[6] Akhtar M T, Mitsuhashi W, James C J. Employing spatially constrained ICA and wavelet denoising, for automatic removal of artifacts from multichannel EEG data. Signal Processing, 2012, 92(2):401-416 doi: 10.1016/j.sigpro.2011.08.005
[7] Yan J H, Lu L. Improved Hilbert-Huang transform based weak signal detection methodology and its application on incipient fault diagnosis and ECG signal analysis. Signal Processing, 2014, 98:74-87 doi: 10.1016/j.sigpro.2013.11.012
[8] Boffetta G, Cencini M, Falcioni M, Vulpiani A. Predictability:a way to characterize complexity. Physics Reports, 2002, 356(6):367-474 doi: 10.1016/S0370-1573(01)00025-4
[9] Hu J, Gao J B, Tung W W. Characterizing heart rate variability by scale-dependent Lyapunov exponent. Chaos, 2009, 19(2):Article No. 028506 http://cn.bing.com/academic/profile?id=784de32816f02e68e36e30c568cec669&encoded=0&v=paper_preview&mkt=zh-cn
[10] Aboy M, Hornero R, Abásolo D, Álvarez D. Interpretation of the Lempel-Ziv complexity measure in the context of biomedical signal analysis. IEEE Transactions on Biomedical Engineering, 2006, 53(11):2282-2288 doi: 10.1109/TBME.2006.883696
[11] Tabor M. Chaos and Integrability in Nonlinear Dynamics:An Introduction. New York, USA:Wiley, 1989.
[12] Lee J, Wu F J, Zhao W Y, Ghaffari M, Liao L X, Siegel D. Prognostics and health management design for rotary machinery systems——reviews, methodology and applications. Mechanical Systems and Signal Processing, 2014, 42(1-2):314-334 https://www.researchgate.net/publication/258440016_Prognostics_and_health_management_design_for_rotary_machinery_systemsReviews_methodology_and_applications
[13] Shilnikov L P, Shilnikov A L, Turaev D V, Chua L O. Methods of Qualitative Theory in Nonlinear Dynamics, Part Ⅰ. Singapore:World Scientific, 2001.
[14] Shilnikov L P, Shilnikov A L, Turaev D V, Chua L O. Methods of Qualitative Theory in Nonlinear Dynamics, Part Ⅱ. Singapore:World Scientific, 2001.
[15] Wang C, Hill D J. Learning from neural control. IEEE Transactions on Neural Networks, 2006, 17(1):130-146 http://d.old.wanfangdata.com.cn/Periodical/kzllyyy200403025
[16] Wang C, Hill D J. Deterministic Learning Theory for Identification, Recognition, and Control. Boca Raton, FL, USA:CRC Press, 2009.
[17] 王聪, 陈填锐, 刘腾飞.确定学习与基于数据的建模及控制.自动化学报, 2009, 35(6):693-706 http://www.aas.net.cn/CN/abstract/abstract13333.shtml

Wang Cong, Chen Tian-Rui, Liu Teng-Fei. Deterministic learning and data-based modeling and control. Acta Automatica Sinica, 2009, 35(6):693-706 http://www.aas.net.cn/CN/abstract/abstract13333.shtml
[18] Wang C, Chen T R. Rapid detection of small oscillation faults via deterministic learning. IEEE Transactions on Neural Networks, 2011, 22(8):1284-1296 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=JJ0222163137
[19] 王聪, 文彬鹤, 司文杰, 彭滔, 袁成志, 陈填锐, 林文愉, 王勇, 侯安平.轴流压气机旋转失速建模与检测, Ⅰ:基于确定学习理论与高阶Moore-Greitzer模型的研究.自动化学报, 2014, 40(7):1265-1277 http://www.aas.net.cn/CN/abstract/abstract18397.shtml

Wang Cong, Wen Bin-He, Si Wen-Jie, Peng Tao, Yuan Cheng-Zhi, Chen Tian-Rui, Lin Wen-Yu, Wang Yong, Hou An-Ping. Modeling and detection of rotating stall in axial flow compressors, Part Ⅰ:investigation on high-order M-G models via deterministic learning. Acta Automatica Sinica, 2014, 40(7):1265-1277 http://www.aas.net.cn/CN/abstract/abstract18397.shtml
[20] Wang C, Dong X D, Ou S X, Wang W, Hu J M, Yang F F. A new method for early detection of myocardial ischemia:cardiodynamicsgram (CDG). Science China Information Sciences, 2016, 59(1):1-11 http://cn.bing.com/academic/profile?id=c35a3986129f1930685efd09e6629ffc&encoded=0&v=paper_preview&mkt=zh-cn
[21] Lempel A, Ziv J. On the complexity of finite sequences. IEEE Transactions on Infromation Theory, 1976, 22(1):75-81 doi: 10.1109/TIT.1976.1055501
[22] Kaspar F, Schuster H G. Easily calculable measure for the complexity of spatiotemporal patterns. Physical Review A, 1987, 36(2):842-848 doi: 10.1103/PhysRevA.36.842
[23] Rapp P E, Cellucci C J, Korslund K E, Watanabe T A, Jiménez-Moñtano M A. Effective normalization of complexity measurements for epoch length and sampling frequency. Physical Review E, 2001, 64(1):Article No. 016209 doi: 10.1103-PhysRevE.64.016209/
[24] Out H H, Sayood K. A new sequence distance measure for phylogenetic tree construction. Bioinformatics (Oxford, England), 2003, 19(16):2122-2130 doi: 10.1093/bioinformatics/btg295
[25] Yan R Q, Gao R X. Complexity as a measure for machine health evaluation. IEEE Transaction on Instrumentation and Measurement, 2004, 53(4):1327-1334 doi: 10.1109/TIM.2004.831169
[26] Savageau M A. Parameter sensitivity as a criterion for evaluating and comparing the performance of biochemical systems. Nature, 1971, 229(5286):542-544 doi: 10.1038/229542a0
[27] Wu W H, Wang F S, Chang M S. Dynamic sensitivity analysis of biological systems. BMC Bioinformatics, 2008, 9(Suppl 12):S17 doi: 10.1186/1471-2105-9-S12-S17
[28] Wang P, Lv J H, Ogorzalek M J. Global relative parameter sensitivities of the feed-forward loops in genetic networks. Neurocomputing, 2012, 78(1):155-165 doi: 10.1016/j.neucom.2011.05.034
[29] Lu B Y, Yue H. Developing objective sensitivity analysis of periodic systems:case studies of biological oscillators. Acta Automatica Sinica, 2012, 38(7):1065-1073
[30] Varma A, Morbidelli M, Wu H. Parametric Sensitivity in Chemical Systems. Cambridge:Cambridge University Press, 1999.
[31] Kolmogorov A N. Three approaches to the quantitative definition of information. International Journal of Computer Mathematics, 1968, 2(1-4):157-168 http://d.old.wanfangdata.com.cn/OAPaper/oai_arXiv.org_quant-ph%2f9907035
[32] Zhang X S, Roy R J, Jensen E W. EEG complexity as a measure of depth of anesthesia for patients. IEEE Transactions on Biomedical Engineering, 2001, 48(12):1424-1433 doi: 10.1109-10.966601/
[33] Sen A K. Complexity analysis of riverflow time series. Stochastic Environmental Research and Risk Assessment, 2009, 23(3):361-366 doi: 10.1007/s00477-008-0222-x
[34] Hong H, Liang M. Fault severity assessment for rolling element bearings using the Lempel-Ziv complexity and continuous wavelet transform. Journal of Sound and Vibration, 2009, 320(1-2):452-468 doi: 10.1016/j.jsv.2008.07.011
[35] Hu J, Gao J B, Principe J C. Analysis of biomedical signals by the Lempel-Ziv complexity:the effect of finite data size. IEEE Transactions on Biomedical Engineering, 2006, 53(12):2606-2609 http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=4359967&arnumber=4015609
[36] Estevez-Rams E, Serrano R L, Fernández B A, Reyes I B. On the non-randomness of maximum Lempel-Ziv complexity sequences of finite size. Chaos, 2013, 23(2):023118 doi: 10.1063/1.4808251
[37] Amigo J M, Kennel M B. Variance estimators for the Lempel-Ziv entropy rate estimator. Chaos, 2006, 16(4):Article No. 043102 http://cn.bing.com/academic/profile?id=70e9b7ddae6db22c4223ffe9937ff000&encoded=0&v=paper_preview&mkt=zh-cn
[38] Estevezrams E, Loraserrano R, Nunes C A J, Aragónfernán-dez B. Lempel-Ziv complexity analysis of one dimensional cellular automata. Chaos, 2015, 25(12):Article No. 123106 doi: 10.1063/1.4936876
[39] Li J K, Song X R, Yin K. Discrete capability of the Lempel-Ziv complexity algorithm on a vibration sequence. Chinese Physics Letters, 2010, 27(6):Article No. 060502 http://cn.bing.com/academic/profile?id=199740929bfa271da53ff6474b09c199&encoded=0&v=paper_preview&mkt=zh-cn
[40] Radhakrishnan N, Wilson J D, Loizou P C. An alternate partitioning technique to quantify the regularity of complex time series. International Journal of Bifurcation and Chaos, 2000, 10(7):1773-1779 doi: 10.1142/S0218127400001092
[41] Sarlabous L, Torres A, Fiz J A, Morera J, Jané R. Index for estimation of muscle force from mechanomyography based on the Lempel-Ziv algorithm. Journal of Electromyography and Kinesiology, 2013, 23(3):548-557 doi: 10.1016/j.jelekin.2012.12.007
[42] Gray A, Abbena E, Salamon S. Modern Differential Geometry of Curves and Surfaces with Mathematica. Boca Raton:CRC Press, 1998.
[43] Chen D F, Wang C, Dong X D. Modeling of nonlinear dynamical systems based on deterministic learning and structural stability. Science China Information Sciences, 2016, 59(9):Article No. 92202 http://kns.cnki.net/KCMS/detail/detail.aspx?filename=JFXG201609008&dbname=CJFD&dbcode=CJFQ
[44] Rössler O E. An equation for continuous chaos. Physics Letters A, 1976, 57(5):397-398 doi: 10.1016/0375-9601(76)90101-8
[45] Chen G R, Dong X N. From Chaos to Order:Methodologies, Perspectives, and Applications. Singapore:World Scientific, 1998.
[46] Paduano J D. Analysis of compression system dynamics. Active Control of Engine Dynamics, 2002, 8:1-36 http://d.old.wanfangdata.com.cn/OAPaper/oai_arXiv.org_cond-mat%2f0207321
[47] Kamath C. A risk stratification system to discriminate congestive heart failure patients using multivalued coarse-graining Lempel-Ziv complexity. Journal of Engineering Science and Technology, 2015, 10(1):12-24