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信息论中各种熵的matlab实现，其中包括自信息量，互信息量，条件熵，联合熵，冗余度等等的计算。-various information theory entropy Matlab achieved, which include the volume of information, mutual information, the conditional entropy, Joint entropy, and so on the redundancy terms.
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Joaquin Goñ i <jgoni@unav.es> &
Iñ igo Martincorena <imartincore@alumni.unav.es>
University of Navarra - Dpt. of Physics and Applied Mathematics &
Centre for Applied Medical Research. Pamplona (Spain).
December 13th, 2
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一个计算信息熵的完整功能类。设计互信息，熵，信息增益，条件熵等等功能。-A calculation of the full functionality of class information entropy. Design of mutual information, entropy, information gain, conditional entropy and more.
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用于求单个符号的信息熵、条件熵、联合熵以及互信息量-Used to seek information on a single symbol entropy, conditional entropy, joint entropy and mutual information
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1928年, George D. Birkhoff提出了著名的美学度量公式measure = order/complexity.但是order和complexity具体如何计算并没有给出。本文在Shannon信息论的基础上，提出了基于Shannon entropy和kolmogorov complexity的美学度量。作者认为他们“on a promising track with a sound theoretical basis, which not only extends but wil
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熵与条件熵，疑义度，噪声熵，互信息等计算程序熵与条件熵，疑义度，噪声熵，互信息等计算程序-Entropy and conditional entropy, equivocation, noise Entropy, mutual information, and procedures for Entropy and conditional entropy calculation, doubt, noise Entropy, mutual information calculation progra
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This matlab codes calculates the mutual information and the conditional mutual information based on k-nearest neighbor algorithm.
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熵,联合熵,条件熵,平均互信息量的通用计算程序-Entropy, joint entropy, conditional entropy, average mutual information of the general-purpose computer program
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图像配准在医学图像处理领域是一项重要的技术，对临床诊断和治疗起着越来越重要的作用。尽管对
这方面的研究已经展开多年，但目前的主要方法仍然存在不足之处，急需改进，以便更好的应用于临床实践。
本文主要针对现在流行的基于最大互信息量的配准方法展开讨论和研究。在此基础上提出了相同重叠区域下的配准框架，在此框架下，将一些统计相似性配准算法统一为基于最小条件熵的图像配准算法。通常称为归一化互信息配准的方法。-Image registration in medical image processing
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随机产生信源概率空间和信道转移概率，计算熵，条件熵、联合熵、平均互信息，信道容量-Randomly generated source transition probability and probability space channel, calculate the entropy, conditional entropy, joint entropy, the average mutual information, channel capacity
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conditional entropy, entropy, joint entropy, mutual information, relative entropy basic features are implemented in matlab approach
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此代码为计算离散随机变量的熵、联合熵、条件熵、互信息的 Matlab 程序(This code is a matlab program for calculating entropy, joint entropy, conditional entropy and mutual information of discrete random variables)
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