Title :
Singular value decomposition-based MA order determination of non-Gaussian ARMA models
Author :
Zhang, Xian-Da ; Zhang, Yuan-Sheng
Author_Institution :
Changcheng Inst. of Metrol. & Meas., Beijing, China
fDate :
8/1/1993 12:00:00 AM
Abstract :
Singular-value-decomposition (SVD)-based moving-average (MA) order determination of non-Gaussian processes using higher-order statistics is addressed. It is shown that the MA order determination of autoregressive moving-average (ARMA) models is equivalent to the rank determination of a certain error matrix, and a SVD approach is proposed. Its simplified form is applied to pure MA models. To improve the robustness of the order selection, a combination of the SVD and the product of diagonal entries (PODE) test is proposed. Some interesting applications of the two SVD approaches are presented, and simulations verify their performance
Keywords :
parameter estimation; signal processing; statistical analysis; ARMA models; MA order determination; SVD; autoregressive moving-average; cumulants; error matrix; higher-order statistics; nonGaussian processes; product of diagonal entries; rank determination; singular value decomposition; Additive noise; Autocorrelation; Gaussian noise; Gaussian processes; Higher order statistics; Phase estimation; Robustness; Spectral analysis; System identification; Testing;
Journal_Title :
Signal Processing, IEEE Transactions on
