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通过matlab代码，gmcalab 快速广义的形态分量分析，基于负熵最大的独立分量分析。- By matlab code, gmcalab fast generalized form component analysis, Based on negative entropy largest independent component analysis.
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借鉴了主成分分析算法（PCA），采用波束成形技术的BER计算，基于SVPWM的三电平逆变的matlab仿真。- It draws on principal component analysis algorithm (PCA), By applying the beam forming technology of BER Based on SVPWM three-level inverter matlab simulation.
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通过matlab代码，基于负熵最大的独立分量分析，用于图像处理的独立分量分析。- By matlab code, Based on negative entropy largest independent component analysis, Independent component analysis for image processing.
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Kernel Entropy Component Analysis,KECA方法的作者R. Jenssen自己写的MATLAB代码，文章发表在2010年5月的IEEE TPAMI上面-Kernel Entropy Component Analysis, by R. Jenssen, published in IEEE TPAMI 2010.(We introduce kernel entropy component analysis (kernel ECA) as a new method fo
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