• DocumentCode
    2505826
  • Title

    Parameter estimation of short-time multi-component signals using damped-amplitude & polynomial-frequency model

  • Author

    Li, Z. ; Martin, N. ; Vieira, M. ; Gueguen, P.

  • Author_Institution
    Dept. Images Signal, Gipsa-Lab., St. Martin d´´Hères, France
  • fYear
    2011
  • fDate
    28-30 June 2011
  • Firstpage
    545
  • Lastpage
    548
  • Abstract
    This paper concerns the parameter estimation of multi-component damped oscillations having non-linear frequency. In this paper, the instantaneous frequency is approximated by polynomials while the amplitude is characterized by damped exponentials to connect directly to its physical interpretations. A maximum likelihood procedure is developed via an adaptive simulated annealing technique which helps to speed up the convergence. Results on simulated signals show that the proposed algorithm is more efficient than the algorithm based on polynomial amplitude models, and allows the estimation of damping coefficients over a very short time duration. Finally, the proposed algorithm is applied for characterizing the ambient vibrations of a building.
  • Keywords
    damping; maximum likelihood estimation; oscillations; parameter estimation; polynomials; signal representation; simulated annealing; adaptive simulated annealing technique; ambient vibration; damped exponential; damped-amplitude model; damping coefficient estimation; instantaneous frequency; maximum likelihood procedure; multicomponent damped oscillation; nonlinear frequency; parameter estimation; polynomial amplitude model; polynomial-frequency model; short-time multicomponent signal; signal representation; Adaptation models; Damping; Estimation; Frequency modulation; Polynomials; Signal to noise ratio; Simulated annealing; Adaptive simulated annealing; Damped amplitude; Maximum likelihood; Polynomial phase signal; Time-frequency;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Statistical Signal Processing Workshop (SSP), 2011 IEEE
  • Conference_Location
    Nice
  • ISSN
    pending
  • Print_ISBN
    978-1-4577-0569-4
  • Type

    conf

  • DOI
    10.1109/SSP.2011.5967755
  • Filename
    5967755