By Topic

Chaotic simulated annealing algorithm applied to ERP dipole localization [EEG signal processing]

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Dezhong Yao ; Sch. of Life Sci. & Technol., Univ. of Electron. Sci. & Technol. of China, Chengdu, China ; Min Zeng ; Yongjie Li

The estimation of dipole parameters of EEG data is a difficult nonlinear optimization problem due to the multiple local minima in the cost function. In this paper, we present and evaluate a more robust and efficient optimization approach, named chaotic simulated annealing (CSA) algorithm. The key idea of CSA is to replace the Gaussian distribution by a chaotic sequence in the conventional standard simulated annealing (SSA). The effectiveness of the new method was confirmed by computer simulation and the preliminary application to the early event-related potential (ERP) of a spatial visual attention experiment. Our results showed that CSA has better robustness and higher feasibility compared with other methods for global optimization problems. Also, the positive results of dipole localization using CSA were achieved for an ERP study.

Published in:

Communications, Circuits and Systems, 2005. Proceedings. 2005 International Conference on  (Volume:2 )

Date of Conference:

27-30 May 2005