However, most existing research results are main about the prediction of the low-dimension chaotic signal, we investigate the prediction of high-dimension chaotic EEG signal in this paper.

但是当前的研究多数是针对低维混沌信号，本文对高维混沌特性的脑电信号的预测研究作初步探讨。

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Texture, recurrent number of object and the area of object are not taken into account in conventional low-dimension image association rules. So the relevant image knowledge can't be mined out.

传统的低维图像关联规则没有考虑纹理要素以及对象的重复出现次数、对象的面积大小，与此相关的图像知识无法挖掘出来。

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This method emphasizes and gives prominence to features which own higher discriminatory power, so the recognition accuracy is enhanced in the low dimension space.

该方法着重强调和突出判别能量较高的特征，从而提高在低维空间的人脸识别正确率。

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