Title :
A method for identifying non-Gaussian parametric model with time-varying coefficients
Author :
Shen, Minfen ; Song, Rong ; Ting, K.H. ; Chan, Francis H Y
Author_Institution :
Sci. Res. Center, Shantou Univ., Guangdong Shantou, China
Abstract :
A method for identifying a non-Gaussian AR model with time-varying parameters is addressed. The proposed approach is based on the application of higher-order spectra (HOS) and wavelet analysis. To solve the problem and identify the characteristics of the time-varying linear system, a time-varying parametric model is proposed as a non-Gaussian AR model. The model coefficients that characterize the time-varying system are the functions of time and can be represented by a family of wavelet basis functions, having the invariant basis coefficients. This method can well track the changes of the model coefficients. The experimental results show the effectiveness of the proposed approach.
Keywords :
autoregressive processes; higher order statistics; parameter estimation; spectral analysis; time-varying systems; wavelet transforms; higher-order spectra; identification; invariant basis coefficients; nonGaussian AR model; nonGaussian parametric model; time-varying coefficients; time-varying linear system; wavelet analysis; wavelet basis functions; Difference equations; Gaussian processes; Linear systems; Parameter estimation; Parametric statistics; Signal processing; System identification; TV; Time varying systems; Wavelet analysis;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
Print_ISBN :
0-7803-7663-3
DOI :
10.1109/ICASSP.2003.1201760
