EEG inverse problem has great significance and importance for both cli nical and research applications. It discusses EEG dipole source localization pro blems solved by nonlinear local optimization methods, such as Lev...EEG inverse problem has great significance and importance for both cli nical and research applications. It discusses EEG dipole source localization pro blems solved by nonlinear local optimization methods, such as Levenberg-Marquar t b. This paper presents the relation between location errors and noise level on c ondition that the source number is known; if the source number is not known, the selected number in model may not equal to the actual one, and a computation is carried out and a corresponding discrimination criteria is proposed. Computer si mulation demonstrates that Levenberg-Marquardt algorithm is better than global methods if the source number is small.展开更多
文摘EEG inverse problem has great significance and importance for both cli nical and research applications. It discusses EEG dipole source localization pro blems solved by nonlinear local optimization methods, such as Levenberg-Marquar t b. This paper presents the relation between location errors and noise level on c ondition that the source number is known; if the source number is not known, the selected number in model may not equal to the actual one, and a computation is carried out and a corresponding discrimination criteria is proposed. Computer si mulation demonstrates that Levenberg-Marquardt algorithm is better than global methods if the source number is small.
