DocumentCode :
3225844
Title :
An approach for identification of non-Gaussian linear system with time-varying parameters
Author :
Shen, Minfen ; Song, Rong ; Ting, K.H. ; Chan, Francis H Y
Author_Institution :
Sci. Res. Center, Shantou Univ., Guangdong, China
Volume :
3
fYear :
2002
fDate :
28-31 Oct. 2002
Firstpage :
1294
Abstract :
A new approach for identification of non-Gaussian linear system with time-varying parameters is addressed in this paper. The proposed method is based on the application of higher-order spectra (HOS) and wavelet analysis. In order to solve the problem and identify the characteristics of the time-varying linear system, a time-varying parametric model is proposed as non-Gaussian AR model. The model parameters that characterize the time-varying system are functions of time and can be represented by a family of wavelet basis functions, of which the corresponding basis coefficients are invariant. This method can well track the changes of the model parameters, and the results show its effectiveness of the proposed approach.
Keywords :
autoregressive processes; linear systems; parameter estimation; time-varying systems; wavelet transforms; HOS; high-order spectra; non-Gaussian AR model; non-Gaussian linear system identification; nonGaussian linear system identification; time-varying linear system; time-varying parametric model; wavelet analysis; wavelet basis functions; Bayesian methods; Costs; Linear systems; Parameter estimation; Parametric statistics; Signal processing; System identification; TV; Time varying systems; Wavelet analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON '02. Proceedings. 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering
Print_ISBN :
0-7803-7490-8
Type :
conf
DOI :
10.1109/TENCON.2002.1182563
Filename :
1182563
Link To Document :
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