Open Access
MATEC Web Conf.
Volume 148, 2018
International Conference on Engineering Vibration (ICoEV 2017)
Article Number 08004
Number of page(s) 6
Section Nonlinearity and Stochasticity in Vibrating Systems
Published online 02 February 2018
  1. Somerville, P., Irikura, K., Graves, R., Sawada, S., Wald, D., Abrahamson, N., Iwasaki, Y., Kagawa, T., Smith, N., Kowada, A. (1999). Characterizing Crustal Earthquake Slip Models for the Prediction of Strong Ground Motion. SeismologicalResearch Letters 70(1), 59-80. [CrossRef] [Google Scholar]
  2. Mai, P. M. and Beroza, G. C. (2002). A spatial random field model to characterize complexity in earthquake slip. Journal of Geophysical Research 187(11), 1-28. [Google Scholar]
  3. Lavallée, D., Liu, P. and Archuleta, R. J. (2006). Stochastic model of heterogeneity in earthquake spatial distribution. Geophysical Journal International 165, 622–640. [CrossRef] [Google Scholar]
  4. RaghuKanth, S. T. G. and Iyengar, R. N. (2009). Engineering source model for strong ground motion. Soil Dynamics and Earthquake Engineering 29, 483-503. [CrossRef] [Google Scholar]
  5. RaghuKanth, S. T. G. (2010). Intrinsic mode functions of earthquake slip distribution. Advances in Adaptive Data Analysis 2(2), 193–215 [CrossRef] [Google Scholar]
  6. Raghukanth, S.T.G. and Sangeetha, S. (2014), A stochastic model for earthquake slip distribution of large events, Geomatics, Natural Hazards and Risk, DOI:10.1080/19475705.2014.941418 [Google Scholar]
  7. Huang, N. E., Shen, Z., Long, S. R., Wu, C. M., Shih, H. H., Zheng, Q., Yen, N. C., Tung, C. C., and Liu, H. H. (1998). The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society London 454, 903–995. [CrossRef] [Google Scholar]
  8. Huang, N. E., Chern, C. C., Huang, K., Salvino, L. W., Long, S. R., and Fan, K. L. (2001). A new spectral representation of earthquake data: Hilbert spectral analysis of station TCU129, Chi-Chi, Taiwan, 21 September 1999. Bulletin of the Seismological Society of America 91(5), 1310-1338. [Google Scholar]
  9. Loh, C. H., Wu, T. C. and Huang, N. E. (2001). Application of the empirical mode decomposition-Hilbert spectrum method to identify near-fault ground-motion characteristics and structural responses. Bulletin of the Seismological Society of America 91, 1339–1357. [CrossRef] [Google Scholar]
  10. Zhang, R. R., Ma, S., Safak, E. and Hartzell, S. (2003). Hilbert-Huang Transform Analysis of Dynamic and Earthquake Motion Recordings. Journal of Engineering Mechanics 129(8), 861–875. [CrossRef] [Google Scholar]
  11. Raghukanth, S.T.G. and Sangeetha, S. (2013), Empirical mode decomposition of earthquake accelerograms, Advances in Adaptive Data Analysis 4(3). DOI: 10.1142/S1793536912500239 [Google Scholar]
  12. Mallikarjuna, C. and Raghukanth, S. T. G. (2010). Forecasting the air traffic for north-east indian cities, Advances in Adaptive Data Analysis 2(1),1-16 [Google Scholar]
  13. Hayes, G.P., Briggs, R.W., Barnhart, W.D., Yeck, W.L., McNamara, D.E., Wald, D.J., Nealy, J.L., Benz, H.M., Gold, R.D., Jaiswal, K.S., Marano, K., Earle, P.S., Hearne, M.G., Smoczyk, G.M., Wald, L.A., Samsonov, S.V., 2015. Characterization of the 2015 Mw 7.8 Nepal (Gorkha) earthquake sequence and its seismotectonic context. Seismological Research Letters 86(6), 1557–1567. [Google Scholar]
  14. Yagi, Y., and Okuwaki, R. (2015). Integrated seismic source model of the 2015 Gorkha, Nepal, earthquake, Geophysical Research Letters 42, 6229–6235. [CrossRef] [Google Scholar]
  15. Lay, T., Ye, L., Koper, K.D., Kanamori, H., (2016). Assessment of teleseismically determined source parameters for the April 25, 2015 Mw7.9 Gorkha, Nepal earthquake and the May 12, 2015 Mw 7.2 aftershock. Tectonophysics 714-715, 4–20. [Google Scholar]
  16. Tung, S., and T. Masterlark (2016), Coseismic slip distribution of the 2015 Mw 7.8 Gorkha, Nepal, earthquake from joint inversion of GPS and InSAR data for slip within a 3-D heterogeneous Domain, Journal of Geophysical Research Solid Earth 121, 3479–3503. [CrossRef] [Google Scholar]
  17. Yue, H., Simon, M., Duputel, Z., Jiang, J., Fielding, E., Liang, C., Owen, S., Moore, A., Riel, B., Ampuero, J.P., Samsonov, S.V. (2016). Depth varying rupture properties during the 2015 Mw 7.8 Gorkha (Nepal) earthquake. Tectonophysics 714-715 (2017) 44–54 [CrossRef] [Google Scholar]
  18. Zhang, L., Lia, J., Liao, W., Wang, Q. (2016). Source rupture process of the (2015) Gorkha, Nepal Mw7.9 earthquake and its tectonic implications. Geodesy and geodynamics 7(2), 124-131 [CrossRef] [Google Scholar]
  19. McNamara, D.E., Yeck, W.L., Barnhart, W.D., Schulte-Pelkum,V., Bergmane.,L., Adhikarid, L.B., Dixit, A., Hough, S.E., Benza, H.M., .Earlea, P.S. (2016).Source modeling of the 2015 Mw 7.8 Nepal (Gorkha) earthquake sequence: Implications for geodynamics and earthquake hazards. Tectonophysics 714-715, 21-30 [CrossRef] [Google Scholar]
  20. Wu, Z., Huang, N. E., and Chen, X. (2009). The multidimensional ensemble empirical mode decomposition method. Advances in Adaptive Data Analysis 1, 339–372. [CrossRef] [Google Scholar]
  21. Huang, N. E., and Wu, Z. 2008. A review on Hilbert-Huang transform: Method and its applications on geophysical studies. Reviews of Geophysics 46, RG2006, doi: 10.1029/2007RG000228. [Google Scholar]
  22. Wu, Z., and Huang, N. E. (2009). Ensemble empirical mode decomposition: A noise-assisted data analysis method. Advances in Adaptive Data Analysis 1, 1–41 [Google Scholar]
  23. Vallee, M. and Bouchan, M. (2004). Imaging coseismic rupture in far Þeld by slip patches. Geophysical Journal International 156, 615-630. [CrossRef] [Google Scholar]
  24. Shinozuka, M., and Deodatis, G. (1998). Stochastic process models for Earthquake source. Probablistic Engineering Mechanics 3(3), 114-123. [CrossRef] [Google Scholar]
  25. Pardo-Igu´ zquiza, E., Chica-Olmo, M., (1993). The Fourier integral method—an efficient spectral method for simulation of random fields. Mathematical Geology 25 (2), 177–217. [CrossRef] [Google Scholar]

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