Browsing by Subject "Source reconstruction"

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    Algebraic acceleration and regularization of the source reconstruction method with the recompressed adaptive cross approximation
    (IEEE, 2014) Kazempour, Mahdi; Gürel, Levent
    We present a compression algorithm to accelerate the solution of source reconstruction problems that are formulated with integral equations and defined on arbitrary three-dimensional surfaces. This compression technique benefits from the adaptive cross approximation (ACA) algorithm in the first step. A further error-controllable recompression is applied after the ACA. The numerical results illustrate the efficiency and accuracy of the proposed method. © 2014 IEEE.
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    ERP source reconstruction by using Particle Swarm Optimization
    (IEEE, 2009) Alp, Yaşar Kemal; Arıkan, Orhan; Karakaş, S.
    Localization of the sources of Event Related Potentials (ERP) is a challenging inverse problem, especially to resolve sources of neural activity occurring simultaneously. By using an effective dipole source model, we propose a new technique for accurate source localization of ERP signals. The parameters of the dipole ERP sources are optimally chosen by using Particle Swarm Optimization technique. Obtained results on synthetic data sets show that proposed method well localizes the dipoles on their actual locations. On real data sets, the fit error between the actual and reconstructed data is successfully reduced to noise level by localizing a few dipoles in the brain.