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为解决PCA不适合多指标综合分析中非线性主成分分析的问题 ,采用核主成分分析 (kpca)方法 ,对我国不同地区 16种腐乳的品质进行了综合评价。
-PCA is not suitable to address the many indicators of a comprehensive analysis of non-linear principal component analysis of the problem, using Kernel Principal Component An
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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
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提出了基于小波核函数的偏最小二乘方法对混沌信号进行了有效拟合，得到了很好的效果。-Based on wavelet kernel function of the partial least squares method of fitting the effective chaotic signal obtained very good results.
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用核回归方法实现图像去噪是目前理论上最先进的图像去噪方法，这里提供的是图像去噪的matlab代码。-Kernel regression method with denoising is theoretically the most advanced image denoising method, here is the matlab code for image denoising.
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【matlab国外编程代做】基于核回归（kernel regression）方法的去模糊MATLAB源码-[Do] matlab programming on behalf of foreign-based kernel regression (kernel regression) method to fuzzy MATLAB can be used as a reference source to learn
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