• DocumentCode
    1183519
  • Title

    Model identification of a noncausal 2-D AR process using a causal 2-D AR model on the nonsymmetric half-plane

  • Author

    Choi, ByoungSeon

  • Author_Institution
    Dept. of Appl. Stat., Yonsei Univ., Seoul, South Korea
  • Volume
    51
  • Issue
    5
  • fYear
    2003
  • fDate
    5/1/2003 12:00:00 AM
  • Firstpage
    1412
  • Lastpage
    1421
  • Abstract
    If a noncausal two-dimensional (2-D) autoregressive (AR) process is bi-causal, there exists a causal 2-D AR process on the nonsymmetric half-plane having the same autocorrelations as the noncausal 2-D AR process. A formula is presented to relate the AR coefficients of the noncausal 2-D AR process with those of the causal 2-D AR process on the nonsymmetric half plane. The 2-D Yule-Walker equations are derived for causal 2-D AR models on the nonsymmetric half plane. A computationally efficient order-recursive algorithm is proposed to solve the 2-D Yule-Walker equations. Using the autocorrelation equivalence relation and the order-recursive algorithm, we can easily identify a noncausal 2-D AR process from its autocorrelations.
  • Keywords
    autoregressive processes; correlation methods; identification; signal processing; 2D Yule-Walker equations; autocorrelation; autoregressive process; bi-causal process; causal 2D AR model; computationally efficient order-recursive algorithm; model identification; noncausal 2D AR process; nonsymmetric half-plane; Autocorrelation; Equations; Image analysis; Image processing; Mathematical model; Stability; Statistics; Sufficient conditions; Two dimensional displays; White noise;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2003.810277
  • Filename
    1194427