论文信息 - Asymptotically Optimal Estimation Of Ma And Arma Parameters Of Non-gaussian Processes From High-order Moments

Asymptotically Optimal Estimation Of Ma And Arma Parameters Of Non-gaussian Processes From High-order Moments

An asymptotically minimum-variance algorithm for estimating the MA and AIUVIA parameters of non Gaussian processes from sample high-order moments is described. The algorithm uses the statistical properties (covariances and cross-covariances) of the sample moments explicitly.

B. Friedlander

[1] M. Rosenblatt,et al. Deconvolution and Estimation of Transfer Function Phase and Coefficients for NonGaussian Linear Processes. , 1982 .

[2] Chrysostomos L. Nikias,et al. Bispectrum estimation: A parametric approach , 1985, IEEE Trans. Acoust. Speech Signal Process..

[3] G. Giannakis. Cumulants: A powerful tool in signal processing , 1987, Proceedings of the IEEE.

[4] G. Giannakis. A Kronecker product formulation of the cumulant based realization of stochastic systems , 1988, 1988 American Control Conference.

[5] Jerry M. Mendel,et al. Adaptive system identification using cumulants , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.

[6] B. Friedlander,et al. Performance analysis of parameter estimation algorithms based on high‐order moments , 1989 .

[7] Benjamin Friedlander,et al. Adaptive IIR algorithms based on high-order statistics , 1989, IEEE Trans. Acoust. Speech Signal Process..

[8] Jerry M. Mendel,et al. Identification of nonminimum phase systems using higher order statistics , 1989, IEEE Trans. Acoust. Speech Signal Process..

[9] Benjamin Friedlander,et al. Asymptotically optimal estimation of MA and ARMA parameters of non-Gaussian processes from high-order moments , 1990 .