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    Rights statement: Open Access funded by Engineering and Physical Sciences Research Council Under a Creative Commons license This is the author’s version of a work that was accepted for publication in Signal Processing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Signal Processing, 125, 2016 DOI: 10.1016/j.sigpro.2016.01.024

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Extraction of instantaneous frequencies from ridges in time-frequency representations of signals

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>08/2016
<mark>Journal</mark>Signal Processing
Volume125
Number of pages14
Pages (from-to)290–303
Publication statusPublished
Early online date10/02/16
Original languageEnglish

Abstract

In signal processing applications, it is often necessary to extract oscillatory components and their properties from time-frequency representations, e.g. the windowed Fourier transform or wavelet transform. The first step in this procedure is to find an appropriate ridge curve: a sequence of amplitude peak positions (ridge points), corresponding to the component of interest and providing a measure of its instantaneous frequency. This is not a trivial issue, and the optimal method for extraction is still not settled or agreed. We discuss and develop procedures that can be used for this task and compare their performance on both simulated and real data. In particular, we propose a method which, in contrast to many other approaches, is highly adaptive so that it does not need any parameter adjustment for the signal to be analysed. Being based on dynamic path optimization and fixed point iteration, the method is very fast, and its superior accuracy is also demonstrated. In addition, we investigate the advantages and drawbacks that synchrosqueezing offers in relation to curve extraction. The codes used in this work are freely available for download.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Signal Processing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Signal Processing, 125, 2016 DOI: 10.1016/j.sigpro.2016.01.024 Open Access funded by Engineering and Physical Sciences Research Council Under a Creative Commons license