Title :
Neural dipole localization by a hybrid nonlinear optimization algorithm
Author :
Ye, Sheng ; Hu, Jie
Author_Institution :
Coll. of Agric. Eng. & Food Sci., Zhejiang Univ., Hangzhou, China
Abstract :
In the MEG inverse problem, the source localization procedure is to obtain dipole parameter solution that produces a calculated field pattern best matching the measured data. Here, a hybrid algorithm is described, i.e., Levenberg-Marquardt (LM) method for a fine scanning near the source area, and quasi-Newton (QN) method for a high-speed coarse scanning over a large area of the head. By a set of simulations, this presented algorithm can be more efficient both in computation time and sensitivity to the iterative initial value.
Keywords :
Newton method; magnetoencephalography; neurophysiology; optimisation; Levenberg-Marquardt method; MEG inverse problem; field pattern; fine scanning; high-speed coarse scanning; hybrid nonlinear optimization algorithm; neural dipole localization; neuromagnetic source; quasi-Newton method; source localization procedure; Agricultural engineering; Brain modeling; Computational modeling; Educational institutions; Head; Hospitals; Inverse problems; Optimization methods; Pattern matching; Valves;
Conference_Titel :
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7508-4
DOI :
10.1109/ICMLC.2002.1167459
