A new recursive pseudo least squares algorithm for ARMA filtering and modeling. II

Author

Prasad, Surendra ; Joshi, Shiv Dutt

Author_Institution

Dept. of Electr. Eng., Indian Inst. of Technol., New Delhi, India

Volume

40

Issue

11

fYear

1992

fDate

11/1/1992 12:00:00 AM

Firstpage

2775

Lastpage

2783

Abstract

For pt.I see ibid., vol.40, no.11, p.2766-74 (Nov. 1992). A recursive algorithm for ARMA (autoregressive moving average) filtering has been developed in a companion paper. These recursions are seen to have a lattice-like filter structure. The ARMA parameters, however, are not directly available from the coefficients of this filter. The problem of identification of the ARMA model from the coefficients of this filter is addressed here. Two new update relations for certain pseudoinverses are derived and used to obtain a recursive least squares algorithm for AR parameter estimation. Two methods for the estimation of the MA parameters are also presented. Numerical results demonstrate the usefulness of the proposed algorithms

Keywords

filtering and prediction theory; least squares approximations; parameter estimation; signal processing; ARMA filtering; ARMA modeling; autoregressive moving average; identification; lattice-like filter structure; parameter estimation; recursive pseudo least squares algorithm; Adaptive filters; Filtering algorithms; Least squares approximation; Least squares methods; Parameter estimation; Recursive estimation; Signal processing algorithms; Technological innovation;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.165664

Filename

165664