An exact forward-backward maximum likelihood autoregressive parameter estimation method

Author

Armour, Bernard ; Morgera, Salvatore D.

Author_Institution

Atlantis Sci. Syst. Group Inc., Ottawa, Ont., Canada

Volume

39

Issue

9

fYear

1991

fDate

9/1/1991 12:00:00 AM

Firstpage

1985

Lastpage

1993

Abstract

A method for obtaining an exact maximum likelihood estimate (MLE) of the autoregressive (AR) parameters is proposed. The method is called the forward-backward maximum likelihood algorithm. Based on a new form of the log likelihood function for a Gaussian AR process, an iterative maximization is used to obtain an MLE of the inverse covariance matrix. The AR parameters are then determined via the normal equations. Experimental results comparing the new method with other popular AR spectrum estimation methods indicate the new method achieves low bias and low variance AR parameter estimates comparable with the existing methods

Keywords

parameter estimation; spectral analysis; Gaussian process; MLE; forward-backward maximum likelihood algorithm; inverse covariance matrix; iterative maximization; log likelihood function; low bias; low variance; maximum likelihood autoregressive parameter estimation; spectrum estimation; Councils; Covariance matrix; Equations; Helium; Iterative algorithms; Maximum likelihood estimation; Parameter estimation; Symmetric matrices;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.134431

Filename

134431