Stochastic Non-Stationary Model for Ground Motion Simulation Based on Higher-Order Crossing of Linear Time Variant Systems

References

• Abed-Meraim, K., Loubaton, P., and Moulines, E. [1997 ] “A subspace algorithm for certain blind identification problems,” Information Theory, IEEE Transactions on 43(2), 499–511.
   Google Scholar
• Alamilla, J., Esteva, L., Garcıa-Perez, J., and Dıaz-Lopez, O. [2001 ] “Evolutionary properties of stochastic models of earthquake accelerograms: Their dependence on magnitude and distance,” Journal of Seismology 5, 1–21.
   Web of Science ®Google Scholar
• Amin, M. and Ang, A. H. [1966 ] “A nonstationary stochastic model for strong motion earthquakes,” (Report No. 306), Urbana, Illinois.
   Google Scholar
• Amiri, G. G., Rad, A. A., and Hazaveh, N. K. [2014 ] “Wavelet‐based method for generating nonstationary artificial pulse‐like near‐fault ground motions,” Computer‐Aided Civil and Infrastructure Engineering 29(10), 758–770.
   Web of Science ®Google Scholar
• Arias, A. Holzapfel, A., and Saragoni, G. R. [1976 ] “An approximate expression for the mean square acceleration of earthquake ground motions,” Fifth World Conference on Earthquake Engineering, Roorkee, India.
   Google Scholar
• Bao, C., Hao, H., Li, Z.-X., and Zhu, X. [2009] “Time-varying system identification using a newly improved HHT algorithm,” Computers & Structures 87(23–24), 1611–1623. doi: http://dx.doi.org/10.1016/j.compstruc.2009.08.016
   Google Scholar
• Baykut, S. and Akgül, T. [2010 ] “Multiscale zero-crossing statistics of intrinsic mode functions for white Gaussian noise,” European Signal Processing Conference (EUSIPCO-2010).
   Google Scholar
• Beresnev, I. and Atkinson, G. [1998 ] “FINSIM: A FORTRAN program for simulating stochastic acceleration,” Seismological Research Letters 69, 27–32.
   Google Scholar
• Boashash, B. [2003 ] Time-frequency signal analysis and processing: A comprehensive reference, Elsevier, Oxford, United Kingdom.
   Google Scholar
• Boashash, B. [1992 ] “Estimating and interpreting the instantaneous frequency of a signal. I. Fundamentals,” Proceedings of the IEEE 80(4), 520–538.
   Web of Science ®Google Scholar
• Bolotin, V. [1960 ] “Statistical theory of the aseismic design of structures,” Proc. Second World Conf. on Earthquake Engineering, Tokyo, Japan, pp. 1365–1374.
   Google Scholar
• Chang, M. K., Kwiatkowski, J. W., Nau, R. F., Oliver, R. M., and Pister, K. S. [1982 ] “Arma models for earthquake ground motions,” Earthquake Engineering and Structural Dynamics 10, 651–662.
   Web of Science ®Google Scholar
• Clough, R. W. and Penzien, J. [1993 ] Dynamics of structures (2nd ed), Computers & Structures Inc., Berkeley, California.
   Google Scholar
• Conte, J. P. and Peng, B. F. [1996 ] “Nonstationay earthquake ground motion model,” 11th World Conference on Earthquake Engineering, Acapulco, Mexico..
   Google Scholar
• Der Kiureghian, A. [1980 ] “Structural response to stationary excitation,” Journal of the Engineering Mechanics Division 106(6), 1195–1213.
   Web of Science ®Google Scholar
• Douglas, J. and Aochi, H. [2008 ] “A survey of techniques for predicting earthquake ground motions for engineering purposes,” Surveys in Geophysics 29, 187–220.
   Web of Science ®Google Scholar
• Feldbauer, C., Pernkopf, F., and Rank, E. [2007] “Adaptive filters,” in A Tutorial for the Course Computational Intelligence, Signal Processing and Speech Communication Laboratory, Inffeldgasse 16c. http://www.igi.tugraz.at/lehre/CI
   Google Scholar
• Feldman, M. [2011a] “Hilbert transform in vibration analysis,” Mechanical Systems and Signal Processing 25(3), 735–802. doi: http://dx.doi.org/10.1016/j.ymssp.2010.07.018
   Google Scholar
• Feldman, M. [2011b] “A signal decomposition or lowpass filtering with Hilbert transform?,” Mechanical Systems and Signal Processing 25(8), 3205–3208. doi: http://dx.doi.org/10.1016/j.ymssp.2011.04.016
   Google Scholar
• Feldman, M. [2012] “Hilbert transform methods for nonparametric identification of nonlinear time varying vibration systems,” Mechanical Systems and Signal Processing(0). doi: http://dx.doi.org/10.1016/j.ymssp.2012.09.003
   Google Scholar
• Ibrahim, S. [1977 ] “Random decrement technique for modal identification of structures,” Journal of Spacecraft and Rockets 14(11), 696–700.
   Web of Science ®Google Scholar
• Jachan, M., Matz, G., and Hlawatsch, F. [2007 ] “Time-frequency ARMA models and parameter estimators for underspread nonstationary random processes,” Signal Processing, IEEE Transactions on 55(9), 4366–4381.
   Web of Science ®Google Scholar
• Juang, J.-N. and Pappa, R. S. [1985 ] “An eigensystem realization algorithm for modal parameter identification and model reduction,” Journal of Guidance, Control, and Dynamics 8(5), 620–627.
   Web of Science ®Google Scholar
• Kedem, B. [1986 ] “Spectral analysis and discrimination by zero-crossings,” Proceedings of the IEEE 74(11), 1477–1493. doi: 10.1109/PROC.1986.13663
   Web of Science ®Google Scholar
• Kiureghian, A. D. and Crempien, J. [1989 ] “An evolutionary model for earthquake ground motion,” Structural Safety 6, 235–246.
   Web of Science ®Google Scholar
• Liu, S.-C. [1970 ] “Evolutionary power spectral density of strong-motion earthquakes,” Bulletin of the Seismological Society of America 60(3), 891–900.
   Web of Science ®Google Scholar
• Lutes, L. D. and Sarkani, S. [2004 ] Random vibrations: analysis of structural and mechanical systems, Butterworth-Heinemann, Burlington, Massachusetts.
   Google Scholar
• Maechling, P. J., Silva, F., Callaghan, S., and Jordan, T. H. [2014 ] “SCEC Broadband Platform: System architecture and software implementation,” Seismological Research Letters 86(1), 27–38.
   Google Scholar
• Mobarakeh, A. A., Rofooei, F. R., and Ahmadi, G. [2002 ] “Simulation of Earthquake Records Using time-varying ARMA(2,1) model,” Probabibilistic Engineering Mechanics 15–34.
   Web of Science ®Google Scholar
• Motazedian, D. and Atkinson, G. [2005 ] “Stochastic finite-fault modeling based on a dynamic corner frequency,” Bulletin of the Seismological Society of America 95(3), 995–1010.
   Web of Science ®Google Scholar
• Moulines, E., Duhamel, P., Cardoso, J.-F., and Mayrargue, S. [1995 ] “Subspace methods for the blind identification of multichannel FIR filters,” Signal Processing, IEEE Transactions on 43(2), 516–525.
   Web of Science ®Google Scholar
• Naeim, F. [1989 ] The seismic design handbook, Chapman & Hall, New York.
   Google Scholar
• Page, C. H. [1952 ] “Instantaneous power spectra,” Journal of Applied Physics 23(1), 103–106.
   Web of Science ®Google Scholar
• Papadimitriou, K. [1990 ] “Stochastic characterization of strong ground motion and application to structural response,” Report No. EERL 90-03, Pasadena, California.
   Google Scholar
• Polhemus, N. W. and Cakmak, A. S. [1981 ] “Simulation of earthquake ground motion using autoregressive moving average (ARMA) models,” Earthquake Engineering & Structural Dynamics 9(4), 343–354.
   Web of Science ®Google Scholar
• Pousse, G., Bonilla, L., Cotton, F., and Margerin, L. [2006 ] “Non stationary stochastic simulation of strong ground motion time histories including natural variability: Application to the K-net Japanese database,” Bulletin of the Seismological Society of America 96(6), 2103–2117.
   Web of Science ®Google Scholar
• Priestley, M. B. [1965 ] “Evolutionary spectra and non-stationary processes,” Journal of the Royal Statistical Society (Statistical Methodology) 27(2), 204–237.
   Google Scholar
• Rezaeian, S. and Der Kiureghian, A. [2008 ] “A stochastic ground motion model with separable temporal and spectral nonstationarities,” Earthquake Engineering & Structural Dynamics 37(13), 1565–1584.
   Web of Science ®Google Scholar
• Rezaeian, S. and Der Kiureghian, A. [2010 ] “Simulation of synthetic ground motions for specified earthquake and site characteristics,” Earthquake Engineering & Structural Dynamics 39(10), 1155–1180.
   Web of Science ®Google Scholar
• Rice, S. O. [1944 ] “Mathematical analysis of random noise,” Bell System Technical Journal 23(3), 282–332.
   Google Scholar
• Rofooei, F., Mobarake, A., and Ahmadi, G. [2001 ] “Generation of artificial earthquake records with a nonstationary Kanai–Tajimi model,” Engineering Structures 23(7), 827–837.
   Web of Science ®Google Scholar
• Saragoni, G. R. and Hart, G. C. [1974 ] “Simulation of artificial earthquakes,” Earthquake Engineering Structural Dynamics 2(3), 249–267.
   Google Scholar
• Shinozuka, M. and Sato, Y. [1967 ] “Simulation of nonstationary random processes,” Journal of Engineering Mechanics 93(1), 11–40.
   Google Scholar
• Stafford, P., Sgobba, S., and Marano, G. [2009 ] “An energy-based envelope function for the stochastic simulation of earthquake accelerograms,” Soil Dynamics and Earthquake Engineering 29, 1123–1133.
   Web of Science ®Google Scholar
• Sun, X., Hartzell, S., and Rezaeian, S. [2015 ] “Ground‐Motion Simulation for the 23 August 2011, Mineral, Virginia, Earthquake Using Physics‐Based and Stochastic Broadband Methods,” Bulletin of the Seismological Society of America 105(5), 2641–2661.
   Google Scholar
• Tsatsanis, M. K. and Giannakis, G. B. [1996 ] “Modelling and equalization of rapidly fading channels,” International Journal of Adaptive Control and Signal Processing 10(2–3), 159–176.
   Web of Science ®Google Scholar
• Tsatsanis, M. K. and Giannakis, G. B. [1997 ] “Subspace methods for blind estimation of time-varying FIR channels,” Signal Processing, IEEE Transactions on 45(12), 3084–3093.
   Web of Science ®Google Scholar
• Vanmarcke, E. H. [1975 ] “On the distribution of the first-passage time for normal stationary random processes,” Journal of Applied Mechanics, 42(1), 215–220.
   Web of Science ®Google Scholar
• Verhaegen, M. and Yu, X. [1995] “A class of subspace model identification algorithms to identify periodically and arbitrarily time-varying systems,” Automatica 31(2), 201–216. doi: http://dx.doi.org/10.1016/0005-1098(94)00091-V
   Google Scholar
• William, H., Shanmugan, K. S., Rappaport, T., and Kosbar, K. [2004 ] “Principles of communication systems simulation with wireless applications,” Prentice Hall Professional Technical Reference, Upper Saddle River, New Jersey.
   Google Scholar
• Yamamoto, Y. and Baker, J. W. [2013 ] “Stochastic model for earthquake ground motion using wavelet packets,” Bulletin of the Seismological Society of America 103(6), 3044–3056.
   Web of Science ®Google Scholar
• Yeh, C. H. and Wen, Y. K. [1990 ] “Modeling of nonstationary ground motion and analysis of inelastic structural response,” Structural Safety 8, 281–298.
   Web of Science ®Google Scholar