Nonstationary statistical tests in time-scale space

Author

Hambaba, Ahmed

Author_Institution

NASA Ames Res. Center, Moffett Field, CA, USA

Volume

6

fYear

2000

fDate

2000

Firstpage

373

Abstract

Detection and estimation of abrupt changes in a nonstationary environment is an important and challenging problem. A statistical test for selecting the order of a nonstationary AR model is presented based on wavelet vanishing moment and predictive least squares principle. The order of the nonstationary AR is estimated at a different resolution level, which makes the order reliable. Its confidence interval is also determined. The test is derived based on the order probability distribution of the wavelet approximation sequence

Keywords

autoregressive processes; fault diagnosis; least squares approximations; probability; signal processing; statistical analysis; wavelet transforms; abrupt changes; aerospace; confidence interval; machine monitoring; nonstationary AR model; nonstationary statistical tests; order probability distribution; predictive least squares; time-scale space; wavelet approximation sequence; wavelet vanishing moment; Band pass filters; Energy resolution; Fourier transforms; Low pass filters; Multiresolution analysis; Signal processing; Signal resolution; Testing; Time frequency analysis; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Aerospace Conference Proceedings, 2000 IEEE

Conference_Location

Big Sky, MT

ISSN

1095-323X

Print_ISBN

0-7803-5846-5

Type

conf

DOI

10.1109/AERO.2000.877913

Filename

877913