Estimating the number of components of a multicomponent nonstationary signal using the short-term time-frequency Rényi entropy

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contributor.author Sucic, V en_US
contributor.author Saulig, Nicoletta en_US
contributor.author Boashash, B en_US
date.accessioned 2012-03-11T18:58:38Z en_US
date.available 2012-03-11T18:58:38Z en_US
date.issued 2011 en_US
identifier.citation Sucic et al.: Estimating the number of components of a multicomponent nonstationary signal using the short-term timefrequency Rényi entropy. EURASIP Journal on Advances in Signal Processing 2011 2011:125. en_US
identifier.uri http://hdl.handle.net/10576/10800 en_US
identifier.uri http://dx.doi.org/10.1186/1687-6180-2011-125
description This article proposes a method for estimating the local number of signals components using the short term Rényi entropy of signals in the time-frequency plane. (Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354). In addition, 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
description.abstract The time-frequency Rényi entropy provides a measure of complexity of a nonstationary multicomponent signal in the time-frequency plane. When the complexity of a signal corresponds to the number of its components, then this information is measured as the Rényi entropy of the time-frequency distribution (TFD) of the signal. This article presents a solution to the problem of detecting the number of components that are present in short-time interval of the signal TFD, using the short-term Rényi entropy. The method is automatic and it does not require a prior information about the signal. The algorithm is applied on both synthetic and real data, using a quadratic separable kernel TFD. The results confirm that the short-term Rényi entropy can be an effective tool for estimating the local number of components present in the signal. The key aspect of selecting a suitable TFD is also discussed. en_US
language.iso en en_US
publisher Springer en_US
subject Time-Frequency Renyi entropy en_US
subject TFRE en_US
subject TFD en_US
subject time-frequency distributions en_US
subject time-frequency signal processing en_US
subject multicomponent estimation en_US
subject non-stationary signals en_US
subject MBD en_US
subject modified B Distribution en_US
subject EMD en_US
subject empirical mode decomposition en_US
subject time-frequency measures en_US
subject time-frequency signal analysis en_US
subject time-frequency features en_US
subject complexity measure en_US
subject IF estimation en_US
subject instantaneous frequency en_US
subject Separable kernel en_US
subject (t,f) plane en_US
subject SPWVD en_US
subject Gabor logon en_US
title Estimating the number of components of a multicomponent nonstationary signal using the short-term time-frequency Rényi entropy en_US
type Article en_US


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