In this paper, kernel independent component analysis (KICA) 's principle and algorithm are introduced, and then the KICA comparison with some other ICA and principal component analysis (PCA) is given.
论文介绍了基于核空间的ICA的原理和基本算法,然后介绍了该算法与典型ICA和主成分分析(PCA)在盲源信号分离中的比较。
On the foundation of the analysis and comparison of the error of the combination forecast and independent forecast, the paper has given the conditions of the former being least.
在分析比较组合预测与单个预测的精度(误差)大小基础上,给出了组合预测精度高于单个预测精度的条件,并给出了组合预测的精度估计公式。
The simple factor analysis of variance and further statistical method of multiple comparison and independent exponent t-test were used.
运用单因子方差分析及进一步的多重比较、立样本t检验的统计方法。
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