A new method of nonstationary time series analysis based on inhomogeneous AR equation

Author

Yokoyama, Yukiko ; Kumazawa, Mineo ; Imanishi, Yuichi ; Mikami, Naoki

Author_Institution

Dept. of Comput. & Inf. Sci., Univ. of Ind. Technol., Kanagawa, Japan

Volume

45

Issue

8

fYear

1997

fDate

8/1/1997 12:00:00 AM

Firstpage

2130

Lastpage

2136

Abstract

We propose a new model for nonstationary time series analysis. The model is of a noise-contaminated signal of an AR system excited by a sequence of an input signal represented in terms of orthogonal functions. We also propose an algorithm that enables us to estimate parameters of the AR part and the input signal simultaneously. The models are finally evaluated by testing the recovery of an output signal. Examples of data analysis of the synthetic time series are shown for the ease in which the input signal is represented by a sequence of wavelets

Keywords

autoregressive processes; data analysis; parameter estimation; sequences; signal processing; time series; wavelet transforms; AR system; data analysis; inhomogeneous AR equation; input signal sequence; noise contaminated signal; nonstationary time series analysis; output signal recovery; parameter estimation; synthetic time series; wavelets sequence; Autoregressive processes; Data analysis; Differential equations; Eigenvalues and eigenfunctions; Information science; Parameter estimation; Stochastic processes; Testing; Time series analysis; Wavelet analysis;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.611233

Filename

611233