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A."],"published-print":{"date-parts":[[2018,8,13]]},"abstract":"<jats:p>\n                    The continuous wavelet transform (CWT) has played a key role in the analysis of time-frequency information in many different fields of science and engineering. It builds on the classical short-time Fourier transform but allows for variable time-frequency resolution. Yet, interpretation of the resulting spectral decomposition is often hindered by smearing and leakage of individual frequency components. Computation of instantaneous frequencies, combined by frequency reassignment, may then be applied by highly localized techniques, such as the synchrosqueezing transform and ConceFT, in order to reduce these effects. In this paper, we present the synchrosqueezing transform together with the CWT and illustrate their relative performances using four signals from different fields, namely the LIGO signal showing gravitational waves, a \u2018FanQuake\u2019 signal displaying observed vibrations during an American football game, a seismic recording of the\n                    <jats:italic>M<\/jats:italic>\n                    <jats:sub>\n                      <jats:italic>w<\/jats:italic>\n                    <\/jats:sub>\n                    8.2 Chiapas earthquake, Mexico, of 8 September 2017, followed by the Irma hurricane, and a volcano-seismic signal recorded at the Popocat\u00e9petl volcano showing a tremor followed by harmonic resonances. These examples illustrate how high-localization techniques improve analysis of the time-frequency information of time-varying signals.\n                  <\/jats:p>\n                  <jats:p>This article is part of the theme issue \u2018Redundancy rules: the continuous wavelet transform comes of age\u2019.<\/jats:p>","DOI":"10.1098\/rsta.2017.0254","type":"journal-article","created":{"date-parts":[[2018,7,9]],"date-time":"2018-07-09T03:35:11Z","timestamp":1531107311000},"page":"20170254","update-policy":"https:\/\/doi.org\/10.1098\/crossmark-policy","source":"Crossref","is-referenced-by-count":77,"title":["Analysis of time-varying signals using continuous wavelet and synchrosqueezed transforms"],"prefix":"10.1098","volume":"376","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1600-6445","authenticated-orcid":false,"given":"Jean Baptiste","family":"Tary","sequence":"first","affiliation":[{"name":"Departamento de Geociencias, Universidad de los Andes, Bogot\u00e1, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2214-6775","authenticated-orcid":false,"given":"Roberto Henry","family":"Herrera","sequence":"additional","affiliation":[{"name":"Department of Physics, University of Alberta, Edmonton, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6416-8839","authenticated-orcid":false,"given":"Mirko","family":"van der Baan","sequence":"additional","affiliation":[{"name":"Department of Physics, University of Alberta, Edmonton, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"175","published-online":{"date-parts":[[2018,7,9]]},"reference":[{"key":"e_1_3_6_2_2","doi-asserted-by":"publisher","DOI":"10.1002\/2014RG000461"},{"key":"e_1_3_6_3_2","first-page":"429","article-title":"Theory of communication: part I. the analysis of information","volume":"93","author":"Gabor D","year":"1946","journal-title":"J. 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