Articles | Volume 25, issue 1
https://doi.org/10.5194/npg-25-175-2018
https://doi.org/10.5194/npg-25-175-2018
Research article
 | 
05 Mar 2018
Research article |  | 05 Mar 2018

A general theory on frequency and time–frequency analysis of irregularly sampled time series based on projection methods – Part 2: Extension to time–frequency analysis

Guillaume Lenoir and Michel Crucifix

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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Guillaume Lenoir on behalf of the Authors (04 Dec 2017)  Author's response   Manuscript 
ED: Publish as is (06 Dec 2017) by Jinqiao Duan
AR by Guillaume Lenoir on behalf of the Authors (07 Dec 2017)  Author's response   Manuscript 
Short summary
There is so far no general framework for handling the continuous wavelet transform when the time sampling is irregular. Here we provide such a framework with the Morlet wavelet, based on the results of part I of this study. We also design a test of significance against a general background noise which encompasses the Gaussian white or red noise. All the analysis tools presented in this article are available to the reader in the Python package WAVEPAL.