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Classification of biomagnetic field patterns by neural networks

机译:神经网络对生物磁场模式的分类

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When analyzing biomagnetic fields, three-dimensional source reconstruction plays an important role. A method is presented which facilitates preprocessing for such a reconstruction. A neural net classifier decides whether from a given magnetoencephalographic map a localization using a given source model can be carried through. The performance in practical applications is compared for various types of networks. Some new information about the properties of the biomagnetic inverse problem is obtained by extracting rules from the trained nets.
机译:在分析生物磁场时,三维源重建起着重要作用。提出了一种方法,其有助于预处理进行这种重建。神经净分类器决定是否可以通过给定的源模型来实现使用给定源模型的定位。对各种类型的网络进行比较实际应用中的性能。关于从训练网的规则提取规则获得了关于生物磁性逆问题的属性的一些新信息。

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