Abstract
Electroencephalography (EEG) is a neuroimaging technique for localizing active sources within the brain, from knowledge of electromagneticmeasurements outside the head. Recognition of point sources from boundary measurements is an ill-posed inverse problem. InEEG, measurements areonly accessible at electrode positions, the number of sources is not known a prior. This paper proposes a comparison between two approaches for EEGsource localization. First method based on Meromorphic approximation techniques in the complex plane and second one belongs to EEG’s methodwhich is processed using Fuzzy C-Means (FCM). Comparison results on simulated data are used to verify the superior of the Meromorphicapproximation with regarding to Fuzzy c-means, due to it provides the way for solving inverse problem of EEG source localization in 3D from boundarymeasurement based on Harmon function in the innermost layer .
Highlights
EEG Source Localization techniques intends to localizing active sources inside the brain from measurements of the electromagnetic field they produce, which can be measured outside the head
By introducing reasonable a priori restrictions, the inverse problem can be solved and the most probable sources in the brain can be accurately localized [3].One of the this assumption is about limitation of number of sources .When a limited number of sources are modelled as pointwise and dipolar, it has been verified that the inverse problem of source estimation has a unique solution [4]
This paper focuses on comparison between two approaches, which, like multiple signal classification (MUSIC) and beamforming, requires no former information on the number of sources
Summary
EEG Source Localization techniques intends to localizing active sources inside the brain from measurements of the electromagnetic field they produce, which can be measured outside the head. This localization problem is commonly referred to as the inverse source problem of electroencephalography. Dipole fitting methods must minimize a non-convex goal function, a result that is unstable with respect to the number of dipoles in the model [6]. When this number is supposed to be known in advance, an algebraic method has been offered in [4], which requires rank computation of related matrices
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