DocumentCode :
300453
Title :
A hybrid approach to time series analysis and spectral estimation
Author :
Liang, Ying-Chang ; Zhang, Xian-Da ; Li, Yan-Da
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Volume :
1
fYear :
1995
fDate :
21-23 Jun 1995
Firstpage :
124
Abstract :
This paper addresses the signal modeling problem in colored noise. As contrasted to the reported literatures in which the modeling of a non-Gaussian ARMA signal corrupted by Gaussian noise is studied, this paper focus on the AR modeling of a Gaussian signal embedded in non-Gaussian ARMA noise. The authors show that after prefiltering the output data via the AR polynomial of the non-Gaussian noise model, a new special higher-order Yule-Walker equation which is based on the correlation of the filtered output process can be used to estimate the parameters of the AR Gaussian signal. Simulation examples are presented to demonstrate the effectiveness of the new approach
Keywords :
Gaussian noise; autoregressive moving average processes; polynomials; signal processing; time series; AR modeling; AR polynomial; Gaussian signal; colored noise; higher-order Yule-Walker equation; hybrid approach; nonGaussian ARMA noise; signal modeling; spectral estimation; time series analysis; Colored noise; Equations; Gaussian noise; Polynomials; Predictive models; Signal analysis; Signal processing; Spectral analysis; Time series analysis; Working environment noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, Proceedings of the 1995
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-2445-5
Type :
conf
DOI :
10.1109/ACC.1995.529221
Filename :
529221
Link To Document :
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