• DocumentCode
    2820316
  • Title

    New Research on Causal Mixed-Phase ARMA Model Order Determination

  • Author

    Wang Shao-shui ; Dai Yong-shou ; Wang Fang

  • Author_Institution
    Coll. of Inf. & Control Eng., China Univ. of Pet., Dongying, China
  • fYear
    2009
  • fDate
    11-13 Dec. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    On the assumption that the ARMA model is causal and nonminimum phase, sample autocorrelation function and sample higher order cumulant are respectively used to form the special matrixes. And then the singular value decomposition (SVD) method is taken to determine the AR order via estimating the effectual rank of the special matrix. The author proposes a new MA model order determination method via combining the information theoretic criteria method and higher-order cumulant method. Numerical simulations demonstrate that the approach proposed in this paper can improve the precision of higher order cumulants based method. And the new approach has great potential value.
  • Keywords
    autoregressive moving average processes; causality; information theory; singular value decomposition; causal mixed-phase ARMA model order determination; higher order cumulant; higher-order cumulant method; information theoretic criteria; nonminimum phase; sample autocorrelation function; singular value decomposition; special matrixes; Additive noise; Autocorrelation; Autoregressive processes; Cost function; Linear algebra; Matrix decomposition; Numerical simulation; Optimization methods; Parameter estimation; Singular value decomposition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4507-3
  • Electronic_ISBN
    978-1-4244-4507-3
  • Type

    conf

  • DOI
    10.1109/CISE.2009.5363529
  • Filename
    5363529