Open Access
Issue
Mechanics & Industry
Volume 18, Number 2, 2017
Article Number 203
Number of page(s) 7
DOI https://doi.org/10.1051/meca/2016066
Published online 26 January 2017
  1. R.E. Kearney, I.W. Hunter, System identification of human joint dynamics, Critical Reviews in Biomedical Engineering 18 (1990) 55–87 [PubMed] [Google Scholar]
  2. M. Baker, Y. Zhao, D. Ludwig, R. Wagner, R.E. Kearney, Time-varying Parallel-cascade System Identification of Ankle Stiffness from Ensemble Data, Proceedings of the 26th Annual international conference of the IEEE EMBS, San Francisco, California, United States, 1st–5th September 2004, pp. 4688–4691 [Google Scholar]
  3. D. Ludwig, T.S. Visser, H. Giesbrecht, R.E. Kearney, Identification of Time-Varying Intrinsic and Reflex Joint Stiffness, IEEE Trans. Biomedical Eng. 58 (2011) 1715–1723 [CrossRef] [Google Scholar]
  4. X. Xu, Z.Y. Shi, Q. You, Identification of linear time-varying systems using a wavelet-based state-space method, Mech. Systems Signal Process. 26 (2012) 91–103 [CrossRef] [Google Scholar]
  5. S.G. Mouroutsos, P.N. Paraskevopoulos, Identification of time-varying linear systems using orthogonal functions, J. Frankl. Inst. 320 (1985) 249–258 [CrossRef] [Google Scholar]
  6. T.S. Morais, V. Steffen, N. Bachschmid, Time-varying parameter identification using orthogonal functions, J. Phys. Conf. Ser. 135 (2008) 102072 [CrossRef] [Google Scholar]
  7. J.H. Chou, I.R. Horng, Identification of time-varying bilinear systems using Legendre series, J. Frankl. Inst. 322 (1986) 353–359 [CrossRef] [Google Scholar]
  8. C. Hwang, T.Y. Guo, Parameter identification of a class of tie-varying systems via orthogonal shifted Legendre polynomials, J. Frankl. Inst. 318 (1984) 56–69 [CrossRef] [Google Scholar]
  9. C. Hwang, T.Y. Guo, Identification of lumped linear time-varying systems via block-pulse functions, Int. J. Cont. 40 (1984) 571–583 [CrossRef] [Google Scholar]
  10. M. Razzaghi, S.D. Lin, Identification of time-varying linear and bilinear systems via Fourier series, Comp. Elec. Eng. 17 (1991) 237–244 [CrossRef] [Google Scholar]
  11. P.R. Clement, Laguerre functions in signal analysis and parameter identification, J. Frankl. Inst. 313 (1982) 85–95 [CrossRef] [Google Scholar]
  12. S.V. Lapin, Identification of time-varying nonlinear systems using Chebyshev polynomials, J. Comp. Appl. Math. 49 (1993) 121–126 [CrossRef] [Google Scholar]
  13. Y.P.Shih, C.C.Liu, Parameter estimation of time-varying systems via Chebyshev polynomials of the second kind, Int. J. Sys. Sci. 17 (1986) 459–464 [CrossRef] [Google Scholar]
  14. P.N. Paraskevopoulos, Chebyshev series approach to system identification, analysis and optimal control, J. Frankl. Inst. 316 (1983) 135–157 [CrossRef] [Google Scholar]
  15. D. Rémond, J. Neyrand, G. Aridon, R. Dufour, On improved use of Chebyshev expansion for mechanical system identification, Mech. Sys. Signal Proc. 22 (2007) 390–407 [CrossRef] [Google Scholar]
  16. C. Chochol, S. Chesné, D. Rémond, An original differentiation tool for identification on continuous structures, J. Sound Vib. 332 (2013) 3338–3350 [CrossRef] [Google Scholar]
  17. F. Martel, D. Rancourt, C. Chochol, Y. St-Amant, S. Chesné, D. Rémond, Time-varying torsional stiffness identification on a vertical beam using Chebyshev polynomials, Mech. Sys. Signal Proc. 54-55 (2015) 481–490 [CrossRef] [Google Scholar]
  18. S. Chesné, F. Martel, C. Chochol, D. Rancourt, D. Rémond. Identification of time varying stiffness using derivative estimator and polynomial basis. ISMA International conference on Noise and Vibration Engineering, Sep 2014, LEUVEN, Belgium, 2014 [Google Scholar]
  19. S. Chesné, C. Chochol, D. Rémond, F. Martel, D. Rancourt. Identification of time varying parameters using numerical differentiation by integration, 21st International Congress on Sound and Vibration, Jul 2014, Beijing, China. pp. 1–8, (2014). [Google Scholar]
  20. H. Akaike, A new look at the statistical model identification, IEEE Trans. Automatic Control 19 (1974) 716–723 [Google Scholar]
  21. K.P. Burnham, D.R. Anderson, Model selection and multimodel inference, Springer, New York, 2002 [Google Scholar]
  22. M.A. Butler, A.A. King, Phylogenetic comparative analysis: A modeling approach for adaptive evolution, Am. Naturalist 164 (2004) 683–695 [CrossRef] [Google Scholar]
  23. B.C. O’Meara, C. Ane, M.J. Sanderson, P.C. Wainwright, Testing for different rates of continuous trait evolution using likelihood, Evolution 60 (2006) 922–933 [CrossRef] [PubMed] [Google Scholar]
  24. D. Posada, K.A. Crandall, Selecting the best-fit model of nucleotide substitution, Systematic Biology 50 (2001) 580–601 [CrossRef] [PubMed] [Google Scholar]
  25. M. Ruzek, J.L. Guyader, C. Pézerat, Information criteria and selection of vibration models, J. Acoust. Soc. Am. 136 (2014) 3040–3050 [CrossRef] [PubMed] [Google Scholar]
  26. J.B. Bodeux, J.C. Golinval, Application of ARMAV models to the identification and damage detection of mechanical and civil engineering structures, Smart Mater. Struct. 10 (2001) 1–10 [CrossRef] [Google Scholar]

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