Journal article
Detecting noise in a time series
Chaos (Woodbury, N.Y.), v 7(3), pp 414-422
Sep 1997
PMID: 12779669
Abstract
A numerical algorithm is presented for estimating whether, and roughly to what extent, a time series is noise corrupted. Using phase-randomized surrogates constructed from the original signal, metrics are defined which can be used to quantify the noise level. A saturation occurs in these metrics at signal to noise ratios (SNRs) of around 0 dB and below, and also at around 20 dB and above. In between these two regions there is a monotonic transition in the value of the metrics from one region to the other corresponding to changes in the SNR. (c) 1997 American Institute of Physics.
Metrics
Details
- Title
- Detecting noise in a time series
- Creators
- C. J. Cellucci - Department of Physics, Bryn Mawr College, Bryn Mawr, Pennsylvania 19010A. M. AlbanoP. E. Rapp - Bryn Mawr CollegeR. A. PittengerR. C. Josiassen
- Publication Details
- Chaos (Woodbury, N.Y.), v 7(3), pp 414-422
- Publisher
- American Institute of Physics (AIP)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Psychiatry
- Web of Science ID
- WOS:A1997XZ24900007
- Scopus ID
- 2-s2.0-0038993576
- Other Identifier
- 991019167746504721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Mathematics, Applied
- Physics, Mathematical