在任何时间点，如果太阳仰角或是太阳方位角的错误或是动量向量的错误超过容忍度时，那么ACS将会为了修正此问题而回到适当的模式。
At any point, if the sun elevation or sun azimuth errors or the momentum vector error exceeds tolerances, the ACS will return to an appropriate mode in order to correct the problem.
特征提取的目的是获取特征数目少且分类错误概率小的特征向量。
The purpose of feature extraction is to obtain feature vectors of few number and low error probability.
本文研究了一种支持向量机(SVM)和基于转换的错误驱动学习相结合的汉语组块识别方法。
The paper presents a method of Chinese chunk recognition based on Support Vector Machines (SVM) and transformation-based error-driven learning.
实验结果表明，基于KPCA特征提取法的支持向量机分类器的分类错误率在这四种分类算法中最低。
The experiment results concludes that the SVM classification method based on KPCA have the better classification effect than the other three.
实验结果表明，基于KPCA特征提取法的支持向量机分类器的分类错误率在这四种分类算法中最低。
The experiment results concludes that the SVM classification method based on KPCA have the better classification effect than the other three.
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