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
Link To Document :
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