Studying the K-L transformation applied in character features extraction.
研究k - L变换在字符特征抽取中的应用。
On the basis of K-L transformation, the class mean is taken account, and thus, the classification ability of the feature is improved obviously.
本文在K - L变换基础上，进一步考虑到均值的贡献，从而明显地提高了标志的识别能力。
A diagnosis example on operation of axlebox of reducer. After K-L transformation, a research on the visualization is proceeded. The results are given to prove feasibility of the algorithm.
文中以汽轮机减速箱轴承运行状态诊断为例，对样本数据经K-L变换后进行可视化研究，分类结果表明了该算法的可行性。
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