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AuthorSucic, Victor
AuthorSaulig, Nicoletta
AuthorBoashash, Boualem
Available date2012-03-11T18:58:38Z
Publication Date2011
Publication NameEURASIP Journal on Advances in Signal Processing
CitationSucic 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.
URIhttp://hdl.handle.net/10576/10800
URIhttp://dx.doi.org/10.1186/1687-6180-2011-125
DescriptionThis 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).
AbstractThe 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.
Languageen
PublisherSpringer
SubjectTime-Frequency Renyi entropy
SubjectTFRE
SubjectTFD
Subjecttime-frequency distributions
Subjecttime-frequency signal processing
Subjectmulticomponent estimation
Subjectnon-stationary signals
SubjectMBD
Subjectmodified B Distribution
SubjectEMD
Subjectempirical mode decomposition
Subjecttime-frequency measures
Subjecttime-frequency signal analysis
Subjecttime-frequency features
Subjectcomplexity measure
SubjectIF estimation
Subjectinstantaneous frequency
SubjectSeparable kernel
SubjectTime-frequency planes
SubjectDirection of arrival
SubjectGabor logon
TitleEstimating the number of components of a multicomponent nonstationary signal using the short-term time-frequency Rényi entropy
TypeArticle


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