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  A comparative study of global optimization approaches to MEG source localization

Jiang, T. Z., Luo, A., Li, X. D., & Kruggel, F. (2003). A comparative study of global optimization approaches to MEG source localization. International Journal of Computer Mathematics, 80(3), 305-324. doi:10.1080/0020716022000009255.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-99B2-7 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002C-457F-6
Genre: Journal Article

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 Creators:
Jiang, Tianzi Z.1, Author              
Luo, A., Author
Li, X. D., Author
Kruggel, F.2, 3, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Department Cognitive Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634563              
3MPI of Cognitive Neuroscience (Leipzig, -2003), The Prior Institutes, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634574              

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Free keywords: Magnetoencephalogram (MEG); Dipoles, Global optimization; Genetic algorithms; Simulated annealing; Tabu search
 Abstract: It is well-known that the problem of MEG source localization can be cast as an optimization problem. So far, there have been many works in which various optimization methods were adopted for source localization. In this paper, we compare the performance of three typical and widely used optimization techniques for a specific MEG source localization problem. We first introduce a hybrid algorithm by combining genetic and local search strategies to overcome disadvantages of conventional genetic algorithms. Second, we apply the tabu search, a widely used optimization method in combinational optimization and discrete mathematics, to source localization. To the best of our knowledge, this is the first attempt in the literature to apply tabu search to MEG/EEG source localization. Third, in order to further compare the performance of the above algorithms, simulated annealing is also applied to MEG source localization problem. The computer simulation results show that our local genetic algorithm is the most effective approach to dipole localization, and the tabu search method is also a very good strategy for this problem.

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Language(s): eng - English
 Dates: 2003
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: eDoc: 239257
ISI: 000182107400004
Other: P6760
DOI: 10.1080/0020716022000009255
 Degree: -

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Title: International Journal of Computer Mathematics
  Other : Int. J. Comput. Math.
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: London : Gordon and Breach Science Publishers
Pages: - Volume / Issue: 80 (3) Sequence Number: - Start / End Page: 305 - 324 Identifier: ISSN: 0020-7160
CoNE: /journals/resource/954925407731