A polynomial-algebraic method for non-stationary TARMA signal analysis

Author

Ben Mrad, R. ; Fassois, S.D. ; Levitt, J.A.

Author_Institution

Dept. of Mech. & Ind. Eng., Univ. of Toronto, Toronto, ON, Canada

fYear

1998

fDate

8-11 Sept. 1998

Firstpage

1

Lastpage

4

Abstract

Time dependent AutoregRessive Moving Average (TARMA) models, with parameters belonging to a sub-space spanned by time-domain functions, offer appropriate representation for a fairly wide class of non-stationary signals. Yet, their estimation is difficult, due to problems related to local extrema and the need for accurate initial guess parameter values. In this paper a Polynomial-Algebraic (P-A) TARMA estimation method is introduced. The P-A method achieves low computational complexity while eliminating the need for initial guess parameter values and avoiding local extrema problems. Its performance is demonstrated via Monte Carlo simulations.

Keywords

Monte Carlo methods; autoregressive moving average processes; polynomials; signal representation; time-domain analysis; Monte Carlo simulations; low computational complexity; nonstationary TARMA signal analysis; nonstationary signal representation; polynomial-algebraic TARMA estimation method; time dependent autoregressive moving average models; time-domain functions; Autoregressive processes; Electronic mail; Estimation; Industrial engineering; Polynomials; Predictive models; Signal analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference (EUSIPCO 1998), 9th European

Conference_Location

Rhodes

Print_ISBN

978-960-7620-06-4

Type

conf

Filename

7089577