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The EEG Signal Process Based on EEMD

机译:基于EEMD的脑电信号处理

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摘要

Hilbert Huang Transform (HHT), which is based on EMD (Empirical Mode Decomposition) and Hilbert transform method, is a new signal analysis method. It suits for analyzing the non-linear and non-stationary signals, such as EEG signal particularly. The traditional EMD method has the Mode Mixing problem. Therefore a new method basing on Ensemble Empirical Mode Decomposition (EEMD) for processing the signal has been approached in this paper. This method can effectively ensure the integrity of signal's mapping in the different regions through adding random white noise component into the original data, and overcome the mode mixing problem of traditional EMD decomposition.
机译:基于EMD(经验模态分解)和Hilbert变换方法的Hilbert Huang变换(HHT)是一种新的信号分析方法。它特别适合分析非线性和非平稳信号,例如EEG信号。传统的EMD方法存在模式混合问题。因此,本文提出了一种基于整体经验模态分解(EEMD)的信号处理新方法。通过在原始数据中加入随机的白噪声分量,可以有效地保证不同区域信号映射的完整性,克服了传统EMD分解的模式混合问题。

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