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

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

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dc.contributor.author Sucic, V
dc.contributor.author Saulig, Nicoletta
dc.contributor.author Boashash, B
dc.date.accessioned 2012-03-11T18:58:38Z
dc.date.available 2012-03-11T18:58:38Z
dc.date.issued 2011
dc.identifier.citation EURASIP Journal on Advances in Signal Processing 2011, 2011:125 en_US
dc.identifier.other doi:10.1186/1687-6180-2011-125
dc.identifier.uri http://hdl.handle.net/10576/10800
dc.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
dc.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
dc.language.iso en en_US
dc.publisher Springer en_US
dc.subject Time-Frequency Renyi entropy en_US
dc.subject TFRE en_US
dc.subject TFD en_US
dc.subject time-frequency distributions en_US
dc.subject time-frequency signal processing en_US
dc.subject multicomponent estimation en_US
dc.subject non-stationary signals en_US
dc.subject MBD en_US
dc.subject modified B Distribution en_US
dc.subject EMD en_US
dc.subject empirical mode decomposition en_US
dc.subject time-frequency measures en_US
dc.subject time-frequency signal analysis en_US
dc.subject time-frequency features en_US
dc.subject complexity measure en_US
dc.subject IF estimation en_US
dc.subject instantaneous frequency en_US
dc.subject Separable kernel en_US
dc.subject (t,f) plane en_US
dc.subject SPWVD en_US
dc.subject Gabor logon en_US
dc.title Estimating the number of components of a multicomponent nonstationary signal using the short-term time-frequency Rényi entropy en_US
dc.type Article en_US

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