High resolution sparse estimation of exponentially decaying twodimensional signals
(2014) 22nd European Signal Processing Conference  EUSIPCO 2014 Abstract
 In this work, we consider the problem of highresolution estimation of the parameters detailing a twodimensional (2D) signal consisting of an unknown number of exponentially decaying sinusoidal components. Interpreting the estimation problem as a block (or group) sparse representation problem allows the decoupling of the 2D data structure into a sum of outerproducts of 1D damped sinusoidal signals with unknown damping and frequency. The resulting nonzero blocks will represent each of the 1D damped sinusoids, which may then be used as nonparametric estimates of the corresponding 1D signals; this implies that the sought 2D modes may be estimated using a sequence of 1D optimization problems.
The resulting sparse... (More)  In this work, we consider the problem of highresolution estimation of the parameters detailing a twodimensional (2D) signal consisting of an unknown number of exponentially decaying sinusoidal components. Interpreting the estimation problem as a block (or group) sparse representation problem allows the decoupling of the 2D data structure into a sum of outerproducts of 1D damped sinusoidal signals with unknown damping and frequency. The resulting nonzero blocks will represent each of the 1D damped sinusoids, which may then be used as nonparametric estimates of the corresponding 1D signals; this implies that the sought 2D modes may be estimated using a sequence of 1D optimization problems.
The resulting sparse representation problem is solved using an iterative ADMMbased algorithm, after which the damping and frequency parameter can be estimated by a sequence of simple 1D optimization problems. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/record/4588725
 author
 Adalbjörnsson, Stefan Ingi ^{LU} ; Swärd, Johan ^{LU} and Jakobsson, Andreas ^{LU}
 organization
 publishing date
 2014
 type
 Chapter in Book/Report/Conference proceeding
 publication status
 published
 subject
 keywords
 Sparse signal modeling, Spectral analysis, Sparse reconstruction, Parameter estimation, ADMM.
 host publication
 European Signal Processing Conference
 pages
 5 pages
 publisher
 EURASIP
 conference name
 22nd European Signal Processing Conference  EUSIPCO 2014
 conference location
 Lissabon, Portugal
 conference dates
 20140901  20140905
 external identifiers

 scopus:84911883580
 ISSN
 22195491
 language
 English
 LU publication?
 yes
 id
 3c1af84c2c9b4e06acf11b6e0db026c5 (old id 4588725)
 alternative location
 http://www.eurasip.org/Proceedings/Eusipco/Eusipco2014/HTML/papers/1569925345.pdf
 date added to LUP
 20140917 11:31:33
 date last changed
 20190308 02:34:08
@inproceedings{3c1af84c2c9b4e06acf11b6e0db026c5, abstract = {In this work, we consider the problem of highresolution estimation of the parameters detailing a twodimensional (2D) signal consisting of an unknown number of exponentially decaying sinusoidal components. Interpreting the estimation problem as a block (or group) sparse representation problem allows the decoupling of the 2D data structure into a sum of outerproducts of 1D damped sinusoidal signals with unknown damping and frequency. The resulting nonzero blocks will represent each of the 1D damped sinusoids, which may then be used as nonparametric estimates of the corresponding 1D signals; this implies that the sought 2D modes may be estimated using a sequence of 1D optimization problems. <br/><br> The resulting sparse representation problem is solved using an iterative ADMMbased algorithm, after which the damping and frequency parameter can be estimated by a sequence of simple 1D optimization problems.}, author = {Adalbjörnsson, Stefan Ingi and Swärd, Johan and Jakobsson, Andreas}, issn = {22195491}, keyword = {Sparse signal modeling,Spectral analysis,Sparse reconstruction,Parameter estimation,ADMM.}, language = {eng}, location = {Lissabon, Portugal}, pages = {5}, publisher = {EURASIP}, title = {High resolution sparse estimation of exponentially decaying twodimensional signals}, year = {2014}, }