Analysis of local time-frequency entropy features for nonstationary signal components time supports detection

Sucic, Victor, Saulig, Nicoletta and Boashash, Boualem (2014) Analysis of local time-frequency entropy features for nonstationary signal components time supports detection. Digital Signal Processing: A Review Journal, 34 56-66. doi:10.1016/j.dsp.2014.07.013


Author Sucic, Victor
Saulig, Nicoletta
Boashash, Boualem
Title Analysis of local time-frequency entropy features for nonstationary signal components time supports detection
Journal name Digital Signal Processing: A Review Journal   Check publisher's open access policy
ISSN 1051-2004
1095-4333
Publication date 2014-11-01
Year available 2014
Sub-type Article (original research)
DOI 10.1016/j.dsp.2014.07.013
Volume 34
Start page 56
End page 66
Total pages 11
Place of publication Waltham, MA United States
Publisher Academic Press
Collection year 2015
Language eng
Abstract Identification of different specific signal components, produced by one or more sources, is a problem encountered in many signal processing applications. This can be done by applying the local time-frequency-based Rényi entropy for estimation of the instantaneous number of components in a signal. Using the spectrogram, one of the most simple quadratic time-frequency distributions, the paper proves the local applicability of the counting property of the Rényi entropy. The paper also studies the influence of the entropy order and spectrogram parameters on the estimation results. Numerical simulations are provided to quantify the observed behavior of the local entropy in the case of intersecting components. The causes of decrements in the local number of time supports in the time-frequency plane are also studied. Finally, results are provided to illustrate the findings of the study and its potential use as a key step in multicomponent instantaneous frequency estimation.
Keyword Time-frequency
Rényi entropy
Spectrogram
Component number
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: UQ Centre for Clinical Research Publications
Official 2015 Collection
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 7 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Sun, 19 Oct 2014, 10:47:02 EST by System User on behalf of UQ Centre for Clinical Research