联合熵

  • 网络Joint entropy;combination entropy;MJE
联合熵联合熵
  1. 试验结果表明:用熵、联合熵和平均梯度这3个客观定量指标评价复合效果不仅比目视评价准确有效,而且提供了选择最佳IHS变换用于复合的方法。

    It shows that the quantitative analysis using entropy , joint entropy and average gradient is better than visual quantitative analysis , and provides the way to choose the most suitable IHS transformation for combining images .

  2. 基于交互信息量和联合熵的镜头检测算法

    A Mutual Information and Joint Entropy Based Method for Shot Change Detection

  3. 实验结果显示,该算法获得的融合图像的互信息和联合熵分别达到3.5079和24.732,均优于加权平均融合法、小波融合算法和Laplacian融合算法的融合质量。

    Experimental results demonstrate that the mutual information and the union entropy of the fusion image by our algorithm reach 3.5079 and 24.732 , respectively , which are superior to pixel average algorithm , wavelet fusion algorithm and Laplacian fusion algorithm .

  4. 用联合熵分析短时心率变异信号的非线性动力学复杂性

    Nonlinear Dynamical Complexity Analysis of Short-term Heartbeat Series Using Joint Entropy

  5. 基于多层索引结构的联合熵算法研究

    Solution to joint entropy with multi - layer index structure

  6. 二维模糊向量可信性分布的联合熵及其性质

    Joint Entropy of Credibility Distributions for 2-dimensional Fuzzy Vectors and Its Properties

  7. 基于联合熵的旱涝空间场关联性研究

    Research on the correlation of drought / flood spatial fields by using joint entropy

  8. 基于多元联合熵的航空发动机性能分析

    Performance Analysis of Aero-engine Based on Multi-Joint Entropy

  9. 基于联合熵的多属性匿名度量模型

    A Joint-Entropy-Based Anonymity Metrics Model with Multi-Property

  10. 给出了联合熵和加权广义距离之间平衡参数的确定方法。

    A method is proposed for computing the balance parameter between entropy and the generalized weighted distance .

  11. 联合熵技术用于在边界落入的网格范围内准确地识别聚类的边界点,这样提高了算法的精度。

    Joint entropy is applied to detect boundary points of clusters in these grids and therefore increases algorithm precise .

  12. 基于衡量随机变量之间依赖性的联合熵,我们引入了二值型数据上的熵多样性模式挖掘问题。

    Based on the joint entropy of random variables , we introduce the problem of finding entropy diversity patterns .

  13. 耕地扩张过程与土地质量空间相关关系密切,其联合熵达0.790。

    The correlation between arable land expansion and soil quality was very close and the combine entropy was 0.790 .

  14. 简要地介绍了不确定性、信息熵、联合熵、条件熵、互信息的基本概念。

    The basic concepts of uncertainty , information entropy , united entropy , term entropy and mutual information were introduced briefly .

  15. 有附加噪声时信号的最大互信息谱估计和最大联合熵谱估计

    Maximum Mutual Information ( MMI ) Spectrum Estimation and Maximum Jointed Entropy ( MJE ) Spectrum Estimation in the Presence of Noise

  16. 最后,用联合熵方法来考察短时心率变异性信号的非随机性程度,该方法可以有效的揭示心室对心室纤维性颤动响应的非随机模式。

    At last , using the joint entropy method , the authors uncover nonrandom patterns in the ventricular response to atrial fibrillation .

  17. 通过将它与采用熵和联合熵的评价方法相比较,实验结果表明交互信息量是一种很好的评价方法。

    Compared with the evaluation method of entropy and joint entropy , it was shown that mutual information was a good evaluation criterion .

  18. 本文引入信息论中联合熵的概念,提出了二维随机点的熵误差椭圆指标与三维随机点的熵误差椭球指标。

    In this paper , Union Entropy is introduced while new error indexes , entropy error ellipse and entropy error ellipsoid are presented .

  19. 将两条比对后的序列间的平均交互信息量与它们的联合熵之比作为它们的相似性度量。

    The value of the average mutual information between two aligned sequences divid their joint entropy was used as a measure for their similarity .

  20. 归一化互信息进行配准时,考虑了边缘熵和联合熵的比值,配准结果容易得到最优。

    The normalized mutual information is based on the ratio of the combined entropy and abundance entropy , which makes getting the optimal result easily .

  21. 我们首先介绍联合熵基本理论,用低维的混沌序列进行了检验,证明该方法有效。

    At first , the joint entropy method is demonstrated by applying it to the low-dimensional nonlinear deterministic systems such as logistic map and henon map .

  22. 提出了基于联合熵的多属性匿名度量模型,该模型基于识别性、连接性、跟踪性等匿名属性。

    An anonymity metrics model with three properties based on joint entropy is given in this paper . The three properties are identifiable , linkable and traceable respectively .

  23. 文中对比分析了4种复合方法,并且用熵、联合熵及平均梯度进行了定量评价。

    In this paper , four kinds of methods to integrate SAR and TM imges are analyzed contrastively , and evaluated quantitatively using entropy , joint entropy and average gradient .

  24. 对连续属性离散化的一种方法增类减类算法进行了改进,提出了连续属性联合熵离散化算法。

    I improve a method of algorithm of dispersing successive attribute & increasing class and decreasing class ( ICDC ), put forward the algorithm of dispersing successive attribute with united entropy difference ( UED ) .

  25. 采用熵、联合熵、偏差指数和边缘指数等作为定量指标,对这种流程的融合结果进行了质量评价。

    Entropy , cross entropy , difference index and edge index are employed to estimate the quality of the result image generated by fusing ETM + ( Enhanced Thematic Mapper ) multi-spectrum image and panchromatic image .

  26. 本文详细讨论了最大互信息谱估计和它的性质,提出了另一种新的方法,这种方法应用了最大联合熵原理。

    In this paper the maximum mutual information ( MMI ) Spectrum estimation and its properties are discussed in detail . Another new method is suggested here that uses the maximum jointed entropy ( MJE ) principle .

  27. 通过建立不同随机变量联合熵之间的联系,提出了基于这些上下界的快速多样性模式挖掘算法;在此基础上提出了一个改进的非冗余交互特征子集挖掘算法。

    By establishing serval bounds between entropy of different random variables , we propose some efficient algorithms to find these diversity patterns . We also develop an improved mining algorithm for non-redundant interacting feature subsets . 3 .

  28. 鉴于匿名的随机性和模糊性特点,提出了基于联合熵和最小加权广义距离的模糊模式识别方法,实现了系统匿名等级隶属度向量的离散化。

    According to randomness and fuzziness of anonymity , a fuzzy pattern recognition model is presented based on entropy and least generalized weighted distance , which makes the membership vector of anonymity grades have a desirable dispersive property .

  29. 结果发现:从理论上讲,联合熵是最能反映影像包含的信息量,但是从得出的结果和合成的效果来看并不理想。

    Band combinations by way of all kinds of methods for false color composition are analysed , in conlusion : theoretically speaking , combine entropy can reflect information content of image effectively but the result is not perfect .

  30. 依据光学信息论中的多维随机变量的联合熵、条件熵、平均互信息之间关系和互信息的链式法则,提出了面向挤出中聚合物形态的层析图像处理方法。

    A novel method of tomography image processing is presented for polymer configuration of extrusion , according to the relation of joint entropy , condition entropy , mean mutual information and mutual information chain rule for multidimension random variable in the theory of optics information .