• DocumentCode
    150611
  • Title

    Factorization of processes parametric spectra on the base of multiplicative linear prediction polymodels

  • Author

    Kudriavtseva, N.V.

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Pardubice, Pardubice, Czech Republic
  • fYear
    2014
  • fDate
    15-16 April 2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The linear prediction models can be useful in different tasks of statistical radio engineering. The examples of multimode spectra decomposition on separate components for speech signals, heart rhythmograms, reflected ultrasound signals and hydroacoustic signals have been shown in the paper. The calculation of autoregressive coefficients and parametric power spectrum density of the multiplicative models were derived. Factorization of spectrum estimations is shown using an example of a multiplicative linear prediction model. Using the models that have been developing in our research it is possible to develop the new methods of complex processes analysis. The methods of rhythmogram analysis can be useful for specialists, who create algorithms of cardiogram analysis. More specifically, we consider a method of multimode spectrum factorization in composite process on components using our multiplicative linear prediction polymodels.
  • Keywords
    autoregressive processes; medical signal processing; autoregressive coefficients; heart rhythmograms; hydroacoustic signals; multimode spectra decomposition; multiplicative linear prediction polymodels; parametric power spectrum density; reflected ultrasound signals; speech signals; statistical radio engineering; Autoregressive processes; Estimation; Hafnium; Mathematical model; Maximum likelihood detection; Nonlinear filters; Spectral analysis; autoregression; factorization; linear prediction model; power spectrum density;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Radioelektronika (RADIOELEKTRONIKA), 2014 24th International Conference
  • Conference_Location
    Bratislava
  • Print_ISBN
    978-1-4799-3714-1
  • Type

    conf

  • DOI
    10.1109/Radioelek.2014.6828478
  • Filename
    6828478