使用小波变换的多分辨率源定位

Mingui Sun, Fu-Chrang Tsui, R. Sclabassi
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引用次数: 5

摘要

讨论了小波变换在多通道脑电图电流偶极子源定位中的应用。小波方法自动计算偶极子源定位的临界时间片。与传统方法不同,使用视觉选择的时间片只代表数据中可用信息的一部分,自动计算的时间片是信息保留的。因此,利用每个计算时间片上的参数可以精确地重建脑电信号。此外,小波变换的多分辨率框架提供了一个数学变焦镜头,使人们能够在更大的尺度上选择主要的电源,并在更细的尺度上观察细节。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiresolution source localization using the wavelet transform
The use of the wavelet transform to localize the current dipole sources from the multichannel electroencephalogram (EEG) is discussed. The wavelet approach automatically computes the critical time-slices at which the dipole sources are localized. Unlike the traditional approaches, where visually selected time-slices are used which represent only part of the information available in the data, the automatically computed time-slices are information-preserving. As a result, the EEG can be closely reconstructed using the parameters at each computed time-slice. In addition, the multiresolution framework of the wavelet transform provides a mathematical zoom lens which enables one to select major electrical sources at courser scale levels, and to observe the details at finer scale levels.<>
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