On a fixedpoint algorithm for structured lowrank approximation and estimation of halflife parameters
(2016) 24th European Signal Processing Conference, EUSIPCO 2016 In 2016 24th European Signal Processing Conference, EUSIPCO p.326330 Abstract
We study the problem of decomposing a measured signal as a sum of decaying exponentials. There is a direct connection to sums of these types and positive semidefinite (PSD) Hankel matrices, where the rank of these matrices equals the number of exponentials. We propose to solve the identification problem by forming an optimization problem with a misfit function combined with a rank penalty function that also ensures the PSDconstraint. This problem is nonconvex, but we show that it is possible to compute the minimum of an explicit closely related convexified problem. Moreover, this minimum can be shown to often coincide with the minimum of the original nonconvex problem, and we provide a simple criterion that enables to verify if this... (More)
We study the problem of decomposing a measured signal as a sum of decaying exponentials. There is a direct connection to sums of these types and positive semidefinite (PSD) Hankel matrices, where the rank of these matrices equals the number of exponentials. We propose to solve the identification problem by forming an optimization problem with a misfit function combined with a rank penalty function that also ensures the PSDconstraint. This problem is nonconvex, but we show that it is possible to compute the minimum of an explicit closely related convexified problem. Moreover, this minimum can be shown to often coincide with the minimum of the original nonconvex problem, and we provide a simple criterion that enables to verify if this is the case.
(Less)
 author
 Andersson, Fredrik ^{LU} ; Carlsson, Marcus ^{LU} and Wendt, Herwig
 organization
 publishing date
 20161128
 type
 Chapter in Book/Report/Conference proceeding
 publication status
 published
 subject
 keywords
 Fixedpoint algorithms, Low rank approximation, Structured matrices
 in
 2016 24th European Signal Processing Conference, EUSIPCO
 pages
 5 pages
 publisher
 Institute of Electrical and Electronics Engineers Inc.
 conference name
 24th European Signal Processing Conference, EUSIPCO 2016
 external identifiers

 scopus:85006073740
 ISBN
 9780992862657
 DOI
 10.1109/EUSIPCO.2016.7760263
 language
 English
 LU publication?
 yes
 id
 8422e8c8ce26478c9d595307dc14f42b
 date added to LUP
 20161230 08:35:36
 date last changed
 20170101 08:44:52
@inproceedings{8422e8c8ce26478c9d595307dc14f42b, abstract = {<p>We study the problem of decomposing a measured signal as a sum of decaying exponentials. There is a direct connection to sums of these types and positive semidefinite (PSD) Hankel matrices, where the rank of these matrices equals the number of exponentials. We propose to solve the identification problem by forming an optimization problem with a misfit function combined with a rank penalty function that also ensures the PSDconstraint. This problem is nonconvex, but we show that it is possible to compute the minimum of an explicit closely related convexified problem. Moreover, this minimum can be shown to often coincide with the minimum of the original nonconvex problem, and we provide a simple criterion that enables to verify if this is the case.</p>}, author = {Andersson, Fredrik and Carlsson, Marcus and Wendt, Herwig}, booktitle = {2016 24th European Signal Processing Conference, EUSIPCO }, isbn = {9780992862657}, keyword = {Fixedpoint algorithms,Low rank approximation,Structured matrices}, language = {eng}, month = {11}, pages = {326330}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, title = {On a fixedpoint algorithm for structured lowrank approximation and estimation of halflife parameters}, url = {http://dx.doi.org/10.1109/EUSIPCO.2016.7760263}, year = {2016}, }