• DocumentCode
    1019873
  • Title

    Orthogonalised frequency domain Volterra model for non-Gaussian inputs

  • Author

    Kim, S.B. ; Powers, E.J.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Texas Univ., Austin, TX, USA
  • Volume
    140
  • Issue
    6
  • fYear
    1993
  • fDate
    12/1/1993 12:00:00 AM
  • Firstpage
    402
  • Lastpage
    409
  • Abstract
    An orthogonalised Volterra system model, valid for both non-Gaussian and Gaussian inputs, is presented. The approach is based on ordered sets of conditioned orthogonal higher-order input vectors in the frequency domain, and utilises co-ordinate transformation to relate the orthogonal and nonorthogonal system models. The orthogonal model exhibits no interference effects, thus facilitating physical interpretation of the nonlinear system model. The importance of non-Gaussian excitation in the nonlinear system identification procedure is discussed. The performance of the orthogonalised Volterra model is measured in terms of a generalised nonlinear system coherence function, and compared with the results of the Wiener (for Gaussian input) and Volterra models. The advantages of the orthogonalised Volterra model are illustrated by using it to model the linear and quadratic responses of a tension leg platform subject to random seas, given experimental input-output time series data
  • Keywords
    frequency-domain analysis; nonlinear systems; signal processing; transfer functions; Gaussian inputs; Wiener model; conditioned orthogonal higher-order input vectors; coordinate transformation; experimental input-output time series data; frequency domain; generalised nonlinear system coherence function; identification procedure; interference effects; linear response; nonGaussian excitation; nonGaussian inputs; nonlinear system model; nonorthogonal system models; ordered sets; orthogonalised frequency domain Volterra model; quadratic response; random seas; tension leg platform;
  • fLanguage
    English
  • Journal_Title
    Radar and Signal Processing, IEE Proceedings F
  • Publisher
    iet
  • ISSN
    0956-375X
  • Type

    jour

  • Filename
    260136