In this paper, based on the fourth-order cumulant matrix, a new sub-space decomposition algorithm is proposed for the EEG inverse problem.

基于四阶累积量矩阵的子空间分解，提出了一种新的脑电逆问题算法。

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But the blind estimation algorithm, for example, the sub-space decomposition, is not good for real time estimation because it requires large received signals, and has low estimation convergence rate.

但盲估计算法，如子空间分解法等，需要较大的样本值，收敛速率慢，不利于实时信道估计。

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To this end, this paper presents matching pursuit decomposition combines with sub-space method. The vector space of noisy speech is considered as a noisy speech space added a pure nose space.

为此，本文提出匹配追踪分解与子空间方法结合的方法，带噪语音信号的矢量空间可以认为由一个信号加噪声的子空间和一个纯噪声子空间构成。

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To this end, this paper presents matching pursuit decomposition combines with sub-space method. The vector space of noisy speech is considered as a noisy speech space added a pure nose space.

为此，本文提出匹配追踪分解与子空间方法结合的方法，带噪语音信号的矢量空间可以认为由一个信号加噪声的子空间和一个纯噪声子空间构成。

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