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Parameter estimation of Oscillating Gaussian functions using the scaled reassigned spectrogram

Brynolfsson, Johan LU and Sandsten, Maria LU (2018) In Signal Processing 150. p.20-32
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 non-linear 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 non-linear least squares. The algorithm is evaluated on both simulated and real data.

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author
and
organization
publishing date
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
0165-1684
DOI
10.1016/j.sigpro.2018.03.022
language
English
LU publication?
yes
id
7ddbae00-7dc5-40d4-bc98-652ba50eeaa1
date added to LUP
2018-04-16 15:25:36
date last changed
2022-04-01 23:44:55
@article{7ddbae00-7dc5-40d4-bc98-652ba50eeaa1,
  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 non-linear least squares. The algorithm is evaluated on both simulated and real data.</p>}},
  author       = {{Brynolfsson, Johan and Sandsten, Maria}},
  issn         = {{0165-1684}},
  keywords     = {{Gabor atom; Gaussian functions; Logons; Parameter estimation; Reassigned spectrogram; Transients}},
  language     = {{eng}},
  month        = {{09}},
  pages        = {{20--32}},
  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}},
}