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Combined Analysis-L1 and Total Variation ADMM with Applications to MEG Brain Imaging and Signal Reconstruction

Gao, Rui ; Tronarp, Filip LU and Särkkä, Simo (2018) 26th European Signal Processing Conference, EUSIPCO 2018
Abstract
In this article, we propose an efficient method for solving analysis-l1-TV regularization problems with a multi-step alternating direction method of multipliers (ADMM) approach as the fast solver. Additionally, we apply it to a real-data magnetoen-cephalography (MEG) brain imaging problem as well as to signal reconstruction. In our approach, the inverse problem arising in MEG or signal reconstruction is formulated as an optimization problem which we regularize using a combination of analysis-l1 prior together with a total variation (TV) regularization term. We then formulate an optimization algorithm based on ADMM which can effectively be used to solve the optimization problems. The performance of the algorithm is illustrated in practical... (More)
In this article, we propose an efficient method for solving analysis-l1-TV regularization problems with a multi-step alternating direction method of multipliers (ADMM) approach as the fast solver. Additionally, we apply it to a real-data magnetoen-cephalography (MEG) brain imaging problem as well as to signal reconstruction. In our approach, the inverse problem arising in MEG or signal reconstruction is formulated as an optimization problem which we regularize using a combination of analysis-l1 prior together with a total variation (TV) regularization term. We then formulate an optimization algorithm based on ADMM which can effectively be used to solve the optimization problems. The performance of the algorithm is illustrated in practical scenarios. (Less)
Please use this url to cite or link to this publication:
author
; and
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
26th European Signal Processing Conference (EUSIPCO)
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
26th European Signal Processing Conference, EUSIPCO 2018
conference location
Rome, Italy
conference dates
2018-09-03 - 2018-09-07
external identifiers
  • scopus:85059804897
ISBN
978-9-0827-9701-5
978-90-827970-0-8
978-1-5386-3736-4
DOI
10.23919/EUSIPCO.2018.8553122
language
English
LU publication?
no
id
51553074-348f-47e5-ade5-de5947ee0e04
date added to LUP
2023-08-20 22:51:41
date last changed
2024-05-04 14:29:51
@inproceedings{51553074-348f-47e5-ade5-de5947ee0e04,
  abstract     = {{In this article, we propose an efficient method for solving analysis-l1-TV regularization problems with a multi-step alternating direction method of multipliers (ADMM) approach as the fast solver. Additionally, we apply it to a real-data magnetoen-cephalography (MEG) brain imaging problem as well as to signal reconstruction. In our approach, the inverse problem arising in MEG or signal reconstruction is formulated as an optimization problem which we regularize using a combination of analysis-l1 prior together with a total variation (TV) regularization term. We then formulate an optimization algorithm based on ADMM which can effectively be used to solve the optimization problems. The performance of the algorithm is illustrated in practical scenarios.}},
  author       = {{Gao, Rui and Tronarp, Filip and Särkkä, Simo}},
  booktitle    = {{26th European Signal Processing Conference (EUSIPCO)}},
  isbn         = {{978-9-0827-9701-5}},
  language     = {{eng}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Combined Analysis-L1 and Total Variation ADMM with Applications to MEG Brain Imaging and Signal Reconstruction}},
  url          = {{http://dx.doi.org/10.23919/EUSIPCO.2018.8553122}},
  doi          = {{10.23919/EUSIPCO.2018.8553122}},
  year         = {{2018}},
}