Surrogate data for non-stationary signals

Thumbnail Image

Date

Authors

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

Description

Standard tests for nonlinearity reject the null hypothesis of a Gaussian linear process whenever the data is non-stationary. Thus, they are not appropriate to distinguish nonlinearity from non-stationarity. We address the problem of generating proper surrogate data corresponding to the null hypothesis of an ARMA process with slowly varying coefficients.
4 pages, 4 figures. proceeding for a poster

Keywords

Chaotic Dynamics

Citation

URI

http://salesiana.dossiersoluciones.com/handle/123456789/15708

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/chao-dyn/9904023
 http://arxiv.org/abs/chao-dyn/9904023

Collections

arXiv