Parameter estimation of Oscillating Gaussian functions using the scaled reassigned spectrogram
(2018) In Signal Processing 150. p.2032 Abstract
In this paper we suggest an algorithm for estimation of the parameters detailing Oscillating Gaussian functions. The different components of the signal are first detected in the spectrogram. After this we exploit the fact that a Gaussian function may be perfectly reassigned into one single point given a correct scaling factor, where this scaling factor is a function of the unknown shape parameter of the Gaussian function. The scaled reassignment of the spectrogram is performed using a set of candidate scaling factors and the local Renyi entropy is used to measure the concentration of each component using every candidate scaling factor. The estimates are refined by using nonlinear least squares. The algorithm is evaluated on both... (More)
In this paper we suggest an algorithm for estimation of the parameters detailing Oscillating Gaussian functions. The different components of the signal are first detected in the spectrogram. After this we exploit the fact that a Gaussian function may be perfectly reassigned into one single point given a correct scaling factor, where this scaling factor is a function of the unknown shape parameter of the Gaussian function. The scaled reassignment of the spectrogram is performed using a set of candidate scaling factors and the local Renyi entropy is used to measure the concentration of each component using every candidate scaling factor. The estimates are refined by using nonlinear least squares. The algorithm is evaluated on both simulated and real data.
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 author
 Brynolfsson, Johan ^{LU} and Sandsten, Maria ^{LU}
 organization
 publishing date
 20180901
 type
 Contribution to journal
 publication status
 published
 subject
 keywords
 Gabor atom, Gaussian functions, Logons, Parameter estimation, Reassigned spectrogram, Transients
 in
 Signal Processing
 volume
 150
 pages
 13 pages
 publisher
 Elsevier
 external identifiers

 scopus:85044964755
 ISSN
 01651684
 DOI
 10.1016/j.sigpro.2018.03.022
 language
 English
 LU publication?
 yes
 id
 7ddbae007dc540d4bc98652ba50eeaa1
 date added to LUP
 20180416 15:25:36
 date last changed
 20211006 02:52:21
@article{7ddbae007dc540d4bc98652ba50eeaa1, abstract = {<p>In this paper we suggest an algorithm for estimation of the parameters detailing Oscillating Gaussian functions. The different components of the signal are first detected in the spectrogram. After this we exploit the fact that a Gaussian function may be perfectly reassigned into one single point given a correct scaling factor, where this scaling factor is a function of the unknown shape parameter of the Gaussian function. The scaled reassignment of the spectrogram is performed using a set of candidate scaling factors and the local Renyi entropy is used to measure the concentration of each component using every candidate scaling factor. The estimates are refined by using nonlinear least squares. The algorithm is evaluated on both simulated and real data.</p>}, author = {Brynolfsson, Johan and Sandsten, Maria}, issn = {01651684}, language = {eng}, month = {09}, pages = {2032}, publisher = {Elsevier}, series = {Signal Processing}, title = {Parameter estimation of Oscillating Gaussian functions using the scaled reassigned spectrogram}, url = {http://dx.doi.org/10.1016/j.sigpro.2018.03.022}, doi = {10.1016/j.sigpro.2018.03.022}, volume = {150}, year = {2018}, }