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This is a paragraph on the calculation of current harmonic content of M documents, using MATLAB implementation, high accuracy.

核主成分分析方法，是主成分分析的一种改进算法，是一种非线性的特征提取方法。 (Kernel principal component analysis, is the principal component analysis of an improved algorithm, is a nonlinear feature extraction method.)

很好的MATLAB仿真可以包括通信所有方面所以可以看看(good matlab)

ASVM 工具箱，包含ASVM的核心算法的MATLAB M文件(asvm toolbox)

说明：  非常好用的直方图均衡程序。把图片名字改成自己的图片名字即可。(Histogram equalization )

Bernstein_chebyshev_Lagrange等基函数编写和实现(Bernstein_chebyshev_Lagrange basis functions, such as the preparation and implementation)

K_Means聚类算法matlab实现，包含三个子函数，可用在图像处理中(K_Means clustering algorithm matlab realize, including three sub-functions that can be used in image processing)

在线向量回归分析，有包涵一个例子和内定函数等(On-line vector regression analysis, there is an example of indulgence and unofficially functions, etc.)

说明：  独立成分分析算法降低原始数据噪声，并提取特征值，非常有用得数据去噪程序。(Independent component analysis algorithm reduces the raw data noise, and extract characteristic value, is more helpful data denoising procedure.)

利用matlab软件对图形进行模糊处理，得到运动模糊图像(Using matlab software graphics obfuscated to get motion-blurred images)