SSP'05 -- Proceedings

	IEEE/SP 13th workshop on Statistical Signal Processing July, 17-20, 2005 - Bordeaux - France

Information regarding the paper

Title

Autocorrelation-Based Algorithm For ARMA Model Order Selection In Colored Gaussian Noise

Author(s)

Adnan Al-Smadi

Yarmouk University

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Abstract

In this paper, we have addressed the ARMA model order selection problem for the case of colored Gaussian noise using autocorrelation. The most well known solutions for the ARMA model order problem are the Akiake information criterion (AIC), the minimum description length (MDL), and the minimum eigenvalue (MEV) criteria. In the MEV method, observation and/or modeling error is assumed to be zero-mean white Gaussian. This paper presents a generalization of the original results in the MEV method to the colored Gaussian noise for the second order statistics. Simulations show the performance of the generalization results.