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一种利用中心和结构聚类的稀疏表示图像去噪方法，有不错的效果-a image denoising method with structral clustering and sparse representation, has good effect .
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sar图像去噪的几种新的方法，基于欧几里得距离的聚类分析，cordic算法的matlab仿真。- Several new methods sar image denoising, Clustering analysis based on Euclidean distance, cordic matlab simulation algorithm.
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采用了小波去噪的思想，仿真效果非常好，基于欧几里得距离的聚类分析。- Using wavelet denoising thought, Simulation of the effect is very good, Clustering analysis based on Euclidean distance.
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基于K均值的PSO聚类算法,数据模型归一化，模态振动，sar图像去噪的几种新的方法。- K-means clustering algorithm based on the PSO, Normalized data model, modal vibration, Several new methods sar image denoising.
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Using wavelet denoising thought, Can realize the two-dimensional data clustering, There is a well attenuation curve as input to calculate its seismic waves.
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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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降维，用作聚类算法使用。具有很好效果，可以用作图像去噪(Dimensionality reduction is used as a clustering algorithm. It has good effect and can be used for image denoising.)
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