IF estimation for multicomponent signals using image processing techniques in the time–frequency domain

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Author Rankine, L en_US
Author Mesbah, M en_US
Author Boashash, B en_US
Available date 2011-07-26T05:09:14Z en_US
Available date 2015-02-01T08:24:46Z
Publication Date 2006-03 en_US
Citation Signal Processing Volume 87, Issue 6, June 2007, Pages 1234-1250 en_US
Identifier doi:10.1016/j.sigpro.2006.10.013 en_US
URI http://hdl.handle.net/10576/10723 en_US
URI http://dx.doi.org/10.1016/j.sigpro.2006.10.013
Description This is one of the 1st papers to apply image processing techniques to analyse multicomponent signals with TFDs using image processing techniques (The most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia., and then continuously updated). en_US
Abstract This paper presents a method for estimating the instantaneous frequency (IF) of multicomponent signals. The technique involves, firstly, the transformation of the one-dimensional signal to the two-dimensional time–frequency (TF) domain using a reduced interference quadratic TF distribution. IF estimation of signal components is then achieved by implementing two image processing steps: local peak detection of the TF representation followed by an image processing technique called component linking. The proposed IF estimator is tested on noisy synthetic monocomponent and multicomponent signals exhibiting linear and nonlinear laws. For low signal-to-noise ratio (SNR) environments, a TF peak filtering preprocessing step is used for signal enhancement. Application of the IF estimation scheme to real signals is illustrated with newborn EEG signals. Finally, to illustrate the potential use of the proposed IF estimation method in classifying signals based on their TF components’ IFs, a classification method using least squares data-fitting is proposed and illustrated on synthetic and real signals. en_US
Language en en_US
Publisher Elsevier en_US
Subject instantaneous frequency en_US
Subject multicomponent signals en_US
Subject time-frequency representation en_US
Subject Image Processing en_US
Subject EEG en_US
Subject time-frequency analysis en_US
Subject time-frequency distributions en_US
Subject time-frequency signal processing en_US
Subject quadratic time-frequency distributions en_US
Subject Reduced interference TFDs en_US
Subject seizure en_US
Title IF estimation for multicomponent signals using image processing techniques in the time–frequency domain en_US
Type Article en_US

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