Pering, T.D., Tamburello, G., McGonigle, A.S. et al. (2 more authors) (2014) Correlation of oscillatory behaviour in Matlab using wavelets. Computers & Geosciences, 70. 206 - 212. ISSN 0098-3004
Abstract
Here we present a novel computational signal processing approach for comparing two signals of equal length and sampling rate, suitable for application across widely varying areas within the geosciences. By performing a continuous wavelet transform (CWT) followed by Spearman׳s rank correlation coefficient analysis, a graphical depiction of links between periodicities present in the two signals is generated via two or three dimensional images. In comparison with alternate approaches, e.g., wavelet coherence, this technique is simpler to implement and provides far clearer visual identification of the inter-series relationships. In particular, we report on a Matlab® code which executes this technique, and examples are given which demonstrate the programme application with artificially generated signals of known periodicity characteristics as well as with acquired geochemical and meteorological datasets.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2014 Elsevier Ltd. This is an author produced version of a paper subsequently published in Computers & Geosciences. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Continuous wavelet transform; Wavelets; Spearman's rank correlation; Periodicity; Oscillation; De-noising |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Geography (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 02 Oct 2015 14:53 |
Last Modified: | 23 Jun 2016 00:21 |
Published Version: | http://dx.doi.org/10.1016/j.cageo.2014.06.006 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.cageo.2014.06.006 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:90437 |