On the Choice of Filter Bank Parameters for Wavelet-Packet Identification of Dynamic Systems

  • Henrique Mohallem Paiva
  • Roberto Kawakami Harrop Galvão
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6134)


This paper is concerned with a recently proposed technique for linear system identification in frequency subbands using wavelet-packet filter banks. More specifically, the effect of using different mother wavelets and resolution levels is investigated. The study is based on simulated examples involving the identification of a servomechanism model. The results reveal that the identification outcome can be improved by using wavelet filters with better frequency selectivity, as well as by increasing the number of resolution levels in the filter bank. In this context, the advantages of using wavelet packets instead of standard wavelet decompositions are also discussed.


Wavelet Packets System Identification Filter Banks 


  1. 1.
    Abhayaratne, G.C.K., Jermyn, I.H., Zerubia, J.: Texture-adaptive mother wavelet selection for texture analysis. In: Proc. IEEE International Conference on Image Processing (ICIP), vol. 2, pp. 1290–1293 (2005)Google Scholar
  2. 2.
    Ahuja, N., Lertrattanapanich, S., Bose, N.K.: Properties determining choice of mother wavelet. IEE Proceedings – Visual, Image and Signal Processing 152(5), 659–664 (2005)CrossRefGoogle Scholar
  3. 3.
    Bemporad, A., Garrulli, A., Paoletti, S., Vicino, A.: A bounded-error approach to piecewise affine system identification. IEEE Transactions on Automatic Control 50(10), 1567–1580 (2005)CrossRefGoogle Scholar
  4. 4.
    Bhatia, P., Boudy, J., Andreao, R.V.: Wavelet transformation and pre-selection of mother wavelets for ECG signal processing. In: Proc. 24th IASTED international conference on Biomedical engineering, pp. 390–395 (2006)Google Scholar
  5. 5.
    Chen, H.X., Chua, P.S.K., Lim, G.H.: Adaptive wavelet transform for vibration signal modelling and application in fault diagnosis of water hydraulic motor. Mechanical Systems and Signal Processing 20(8), 2022–2045 (2006)CrossRefGoogle Scholar
  6. 6.
    Daubechies, I.: Ten Lectures on Wavelets. CBMS-NSF Series in Applied Mathematics, vol. (61). SIAM, Philadelphia (1992)zbMATHGoogle Scholar
  7. 7.
    Erlicher, S., Argoul, P.: Modal identification of linear non-proportionally damped systems by wavelet transform. Mechanical Systems and Signal Processing 21(3), 1386–1421 (2007)CrossRefGoogle Scholar
  8. 8.
    Feil, B., Abonyi, J., Szeifert, F.: Model order selection of nonlinear input-output models: a clustering based approach. Journal of Process Control 14(6), 593–602 (2004)CrossRefGoogle Scholar
  9. 9.
    Huang, C.S., Su, W.C.: Identification of modal parameters of a time invariant linear system by continuous wavelet transformation. Mechanical Systems and Signal Processing 21(4), 1642–1664 (2007)CrossRefMathSciNetGoogle Scholar
  10. 10.
    Ljung, L.: System Identification: Theory for the User, 2nd edn. Prentice Hall, Upper Saddle River (1999)Google Scholar
  11. 11.
    Luk, R.W.-P., Damper, R.I.: Non-parametric linear time-invariant system identification by discrete wavelet transforms. Digital Signal Processing 16(3), 303–319 (2006)CrossRefGoogle Scholar
  12. 12.
    Paiva, H.M., Galvão, R.K.H.: Wavelet-packet identification of dynamic systems in frequency subbands. Signal Processing 86(8), 2001–2008 (2006)zbMATHCrossRefGoogle Scholar
  13. 13.
    Paiva, H.M., Galvão, R.K.H.: Wavelet-Packet Identification of Dynamic Systems with Coloured Measurement Noise. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D. (eds.) ICISP 2008. LNCS, vol. 5099, pp. 508–515. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  14. 14.
    Singh, B.N., Tiwari, A.K.: Optimal selection of wavelet basis function applied to ECG signal denoising. Digital Signal Processing 16(3), 275–287 (2006)CrossRefGoogle Scholar
  15. 15.
    Vetterli, M., Kovacevic, J.: Wavelets and Subband Coding. Prentice Hall, Upper Saddle River (1995)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Henrique Mohallem Paiva
    • 1
  • Roberto Kawakami Harrop Galvão
    • 1
  1. 1.CTAInstituto Tecnológico de Aeronáutica – ITASão José dos CamposBrazil

Personalised recommendations