Open Access
Issue
Mécanique & Industries
Volume 11, Number 2, Mars-Avril 2010
Page(s) 105 - 116
DOI https://doi.org/10.1051/meca/2010022
Published online 15 September 2010
  1. G. Shi, S.N. Atluri, Static and dynamic analysis of space frames with non-linear flexible connections, Int. J. Num. Meth. Eng. 28 (1989) 2635–2650 [Google Scholar]
  2. P.D. Moncarz, K.H. Gerstle, Steel frames with non-linear connections, J. Struct. Div. ASCE 107 (1981) 1427–1441 [Google Scholar]
  3. A. Mohebkhaha, A.A. Tasnimia, H.A. Moghadamb, Nonlinear analysis of masonry-infilled steel frames with openings using discrete element method, J. Constr. Steel Res. 64 (2008) 1463–1472 [Google Scholar]
  4. N.M.M. Maia, J.M.M. Silva, Theoretical and Experimental Modal Analysis, Research Study Press LTD, Taunton, England, 1997 [Google Scholar]
  5. J.K. Hammond, P.R. White, The analysis of non-stationary signals using time-frequency methods, J. Sound Vib. 190 (1996) 419–447 [Google Scholar]
  6. S. Mallat, G. Papanicolaou, Z. Zhang, Adaptive covariance estimation of locally stationary processes, Ann. Stat. 28 (1998) 1–47 [Google Scholar]
  7. R. Ceravolo, Time-frequency analysis, in Encyclopedia of Structural Health Monitoring, C. Boller, F.-K. Chang & Y. Fujino (eds.), Wiley & Sons, 2008 [Google Scholar]
  8. P. Bonato, R. Ceravolo, A. D. Stefano, F. Molinari, Use of cross time-frequency estimators for the structural identification in non-stationary conditions and under unknown excitation, J. Sound Vib. 237 (2000) 775–791 [Google Scholar]
  9. R. Ceravolo, Use of instantaneous estimators for the evaluation of structural damping, J. Sound Vib. 274 (2004) 385–401 [Google Scholar]
  10. S. Erlicher, P. Argoul, Modal identification of linear non-proportionally damped systems by wavelet transform, Mech. Sys. Sig. Proc. 21 (2007) 1386–1421 [Google Scholar]
  11. W.B. Collis, P.R. White, J.K. Hammond, Higher-order spectra: the bispectrum and trispectrum, Mechanical Systems and Signal Processing 12 (1998) 375–394 [Google Scholar]
  12. S.B. Kim, E.J. Powers, Estimation of Volterra kernels via higher-order statistical signal processing, Chapter 7 in Higher-Order Statistical Signal Processing B. Boashash, E.J. Powers, A. Zoubir (eds.), Longman/Wiley, Melbourne and New York, 1995 [Google Scholar]
  13. G.V. Demarie, R. Ceravolo, A. D. Stefano, Instantaneous identification of polynomial non-linearity based on Volterra series representation, Key Engineering Materials 293–294 (2005) 703–710 [Google Scholar]
  14. K. Worden, G. Manson, G.R. Tomlinson, A harmonic probing algorithm for the multi-input Volterra series, J. Sound Vib. 201 (1997) 67–84 [Google Scholar]
  15. K. Worden, G. Manson, G.R. Tomlinson, Random vibration of a multi-degree-of-freedom non-linear system using the Volterra series, J. Sound Vib. 226 (1999) 397–405 [Google Scholar]
  16. F. Thouverez, L. Jezequel, Identification of a localized non-linearity, Int. J. Non-Lin. Mech. 33 (1998) 935–945 [Google Scholar]
  17. I. Tawfiq, T. Vinh, Contribution to extension of modal analysis to non-linear structure using Volterra series, Mechanical Systems and Signal Processing 17 (2003) 379–407 [Google Scholar]
  18. A. Chatterjee, N.S. Vyas, Non-linear parameter estimation in multi-degree-of-freedom systems using multi-input Volterra series, Mechanical Systems and Signal Processing 18 (2004) 457–489 [Google Scholar]
  19. M. Schetzen, The Volterra/Wiener theories of non-linear systems, Krieger publishing company, Malabar, FL, 1980 [Google Scholar]
  20. W.J. Rugh, Nonlinear system theory. The Volterra/Wiener approach, 2002 (Web version:) [Google Scholar]
  21. J.A. Vazquez Feijoo, K. Worden, R. Stanway, Associated linear equations for Volterra operators, Mechanical Systems and Signal Processing 19 (2005) 57–69 [Google Scholar]
  22. J.R. Carson, Notes on the theory of modulation, Proc. IEEE 10 (1922) 57–64 [Google Scholar]
  23. W.K. Cloud, D.E. Hudson, Strong motion data from San Fernando, California earthquake of February 9, 1971, California Division of Mines and Geology Bull. 196 (1975) 273–303 [Google Scholar]

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