本文从玻耳兹曼熵和香农熵的概念，推演出熵与信息的互补原理。
This paper presents the principle of complementarity of entropy and information derived from the concepts of L. Boltz mann's entropy and c.
实验结果证明该方法效果良好，优于单独运用香农熵或阈值熵进行辨识的结果。
Experiments show that the proposed method is successful, and is more effective than identification method only using Shannon or threshold entropy.
提出了一种用加权熵代替香农熵的互信息计算方法，并将其应用于图像配准实验。
Weighted entropy instead of Shannon entropy to compute the mutual information is proposed in this paper, and it has been used in medical image registration experiment.
比较了新算法与基于最小交叉熵以及基于传统香农熵的阈值化算法的特点和分割性能。
The new algorithm is compared with a number of traditional algorithms based on Shannon entropy and minimum cross entropy by applying them to various test images.
采用部分体积插值法和香农熵计算得到的互信息，无法避免会出现一些局部极值，可能导致错误的配准。
For the mutual information calculated by partial volume interpolation method and Shannon entropy, certain local extremums are inevitable, which may lead to inaccurate registration.
熵是信号序列信息量的表征，作者在对差压信号的分析中提出了两种基于熵概念的特征——香农熵和阈值熵。
Entropy is a measure of information in signals. Based on the conception of entropy, two new features-Shannon entropy and Threshold entropy are proposed in flow regime identification.
采用一种凸多项式代替模糊熵中的香农函数，提出了基于凸多项式模糊熵的图象阈值方法。
A method of image threshold based on a convex polynomial fuzzy entropy is proposed by replacing Shannon's function of fuzzy entropy with a convex polynomial.
文摘：采用一种凸多项式代替模糊熵中的香农函数，提出了基于凸多项式模糊熵的图象阈值方法。
Abstract: a method of image threshold based on a convex polynomial fuzzy entropy is proposed by replacing Shannon's function of fuzzy entropy with a convex polynomial.
文摘：采用一种凸多项式代替模糊熵中的香农函数，提出了基于凸多项式模糊熵的图象阈值方法。
Abstract: a method of image threshold based on a convex polynomial fuzzy entropy is proposed by replacing Shannon's function of fuzzy entropy with a convex polynomial.
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