Description: The functions include extensive Shannon and nonextensive Tsallis,escort Tsallis,and renyi entropy.
the funcition names start with K_q_ indicate relative entropys
Usage for all the seven functions:
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Size: 2048 |
Author:冯小晶 |
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Description: 这个函数包含广泛的和非广泛的香农Tsallis、escort Tsallis,和renyi 熵. -This function contains a wide range of broad-based and non-Shannon, Tsallis, escort Tsallis, and renyi entropy. The functions include extensive Shannon and nonextensive Tsallis, escort Tsallis, and renyi entropy. The funcition names start with K_q_ indicate rel Platform: |
Size: 3072 |
Author:SHIJIA |
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Description: 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 for data transformation and dimensionality reduction. Kernel ECA reveals structure relating to the Renyi entropy of the input space data set, estimated via a kernel matrix using Parzen windowing. This is achieved by projections onto a subset of entropy preserving kernel principal component analysis (kernel PCA) axes. This subset does not need, in general, to correspond to the top eigenvalues of the kernel matrix, in contrast to the dimensionality reduction using kernel PCA. We show that kernel ECA may produce strikingly different transformed data sets compared to kernel PCA, with a distinct angle-based structure. A new spectral clustering algorithm utilizing this structure is developed with positive results. Furthermore, kernel ECA is shown to be an useful alternative for pattern denoising. Platform: |
Size: 3072 |
Author:johhnny |
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Description: 计算一维向量的Renyi熵，已经设置为头文件，可以直接调用-One-dimensional vector of Renyi entropy, has been set for the header file, you can directly call Platform: |
Size: 1024 |
Author:张晓辉 |
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Description: 实现图像的清晰分割，效果明显,基于图像灰度-梯度构造的二维直方图，在此基础上计算目标与背景的二维Renyi熵-It can handle more types of images and get more accurate shape of the image edgee that pixels gradient information in combination with parameter of Renyi entropy which is adjustable Platform: |
Size: 9216 |
Author:jin |
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Description: 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 for data transformation and dimensionality reduction. Kernel ECA reveals structure relating to the Renyi entropy of the input space data set, estimated via a kernel matrix using Parzen windowing. This is achieved by projections onto a subset of entropy preserving kernel principal component analysis (kernel PCA) axes. This subset does not need, in general, to correspond to the top eigenvalues of the kernel matrix, in contrast to the dimensionality reduction using kernel PCA. We show that kernel ECA may produce strikingly different transformed data sets compared to kernel PCA, with a distinct angle-based structure. A new spectral clustering algorithm utilizing this structure is developed with positive results. Furthermore, kernel ECA is shown to be an useful alternative for pattern denoising.) Platform: |
Size: 8192 |
Author:daxingxing001
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Search - renyi entropy matlab