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
Link To Document :
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