This work focuses on a quasi-linear-in-complexity strategy for a hybrid surface-wire integral equation solver for the electroencephalography forward problem. The scheme exploits a block diagonally dominant structure of the wire self block -- that models the neuronal fibers self interactions -- and of the surface self block -- modeling interface potentials. This structure leads to two Neumann iteration schemes further accelerated with adaptive integral methods. The resulting algorithm is linear up to logarithmic factors. Numerical results confirm the performance of the method in biomedically relevant scenarios.
翻译:这项工作侧重于针对电子脑图学前期问题的混合表面-电线整体方程式解析器的准线性复杂战略。该计划利用了钢丝自块的块形对角主导结构 -- -- 即模拟神经纤维自我互动,以及表面自体块 -- -- 建模界面潜力。这一结构导致两个内生迭代计划以适应性整体方法进一步加速。由此产生的算法直线至对数系数。数字结果证实了生物医学相关情景中该方法的性能。