Fitting ARMA Models to linear non-Gaussian processes using higher order statistics

Authors:
Adnan Al-Smadi;Ahmad Alshamali
Affiliations:
Department of Electronics Engineering, Hijjawi Faculty for Engineering Technology, Yarmouk University, Irbid, Jordan;Department of Electronics Engineering, Hijjawi Faculty for Engineering Technology, Yarmouk University, Irbid, Jordan
Venue:
Signal Processing - Image and Video Coding beyond Standards
Year:
2002

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Abstract

This paper addresses the problem of estimating the parameters of a general autoregressive moving average model using higher order statistics (HOS) when only output data are available. The system is driven by an independent and identically distributed (i.i.d) non-Gaussian process. Simulation results are presented which demonstrate the performance of the new method and compare it with a well-known algorithm based on second order and HOS.