信息熵

xìn xī shānɡ
  • information entropy
信息熵信息熵
  1. 一种基于信息熵的PE文件加壳检测方法

    Another PE File Shell-Adding Detecting Method based on Information Entropy

  2. 基于信息熵的MIX网络关系匿名度量

    Based on the information entropy , the measurement of MIX network anonymity

  3. FPGA连线连接盒中基于信息熵优化的结构设计

    Optimal Design of Topological Structure for FPGA Connection Box Based on Information Entropy

  4. 基于信息熵与未确知测度的MIS综合评价模型研究

    Comprehensive evaluation on MIS based on information entropy and unascertained measure model

  5. 广义信息熵融合RBF异构多神经网络;

    RBF multi-neural network based on generalized information entropy ;

  6. LPG发动机电控供气系统及信息熵理论的应用

    Electronic Control Air-Supplying Systems of LPG Engines And Application of The Information Entropy Theory

  7. 信息熵原理在表面粗糙度Ra不确定度计算中的应用

    Application of Information Entropy Principle to Uncertainty Calculation of the Arithmetic Mean Deviation of Surface Roughness

  8. 第二章研究双模Raman跃迁模型中原子偶极矩信息熵压缩的动力学。

    In chapter 2 , the dynamics of the information entropy squeezing of the atomic dipoles in Raman transition model is investigated .

  9. 基于这种n-gram的统计,本文还进行了汉语信息熵的计算及字、词级知识获取的研究。

    Based on the n gram , the Chinese information entropy and knowledge acquisition at word or phrase level have also been studied .

  10. 本文从信息熵概念着手,利用信息熵的极值性质导出了Boltzmann分布律。

    The paper derives Boltzmann distribution law in terms of the principleof maximum information entropy .

  11. 喷动流化床流动结构的SHANNON信息熵模糊聚类分析

    Application of Shannon entropy and fuzzy cluster in analysis of flow patterns in spout-fluid bed

  12. 然后对源IP地址和源端口进行统计,分别采用均匀随机采样、AMS算法以及本文提出的算法分别估算网络信息熵。

    Then , network information entropy is evaluated using the uniform random sampling , AMS algorithm and the proposed hybrid algorithm respectively .

  13. 突变与Shannon信息熵

    Mutation and Shannon Information Entropy

  14. CALIS中商业数据库文献信息熵化问题研究

    Research on the Entropy of Database Products in the CALIS

  15. 本文设计了通过知识库和信息熵进行特征提取、并以多分支BP网络作为模式识别算法的自适应模式分类器。

    An adaptive classifier , which uses knowledge base and information entropy for feature extraction , and multi-branch BP neural networks ( MBBPNNs ) for pattern recognition , is proposed in this paper .

  16. 比如,在决策树的学习算法中,使用SVM的最大间隔替代最小信息熵,作为启发式信息,这将大大改善决策树的泛化能力。

    For example , the maximal margin of SVM is chosen as a heuristic strategy to substitute minimum entropy in decision tree learning algorithm , which can attain better generalization .

  17. 建立了基于信息熵的TOPSIS工程项目评标模型,其计算简单,结果科学合理。

    TOPSIS model of e-valuation for project bid on information entropy is set up , the calculation method is simple , the result is rational .

  18. 依据信息熵的理论提出了一种将探测数据、RCS样本曲线通过可能性概率进行匹配的目标识别方法。

    Then on the basis of information intelligence quotient , we develop a new target recognition method , which matches the detective data and RCS sample curve though feasible probability .

  19. 决策树的学习算法,比如ID3算法,选用最小信息熵作为启发式信息。

    Minimum entropy is chosen as a heuristic strategy in decision tree ( DT ) learning algorithm such as ID3 .

  20. 根据RoughSet的相关理论,提出了基于条件信息熵的自主式朴素贝叶斯分类方法,该方法结合了选择朴素贝叶斯和加权朴素贝叶斯的优点。

    Based on the theory of rough set , a new Nave Bayes method named Conditional Information Entropy-based Algorithm for Self-learning Nave Bayes ( CIEBASLNB ) was proposed , which combined the merits of selective Nave Bayes ( SNB ) and Weighted Nave Bayes ( WNB ) .

  21. 熵权优属度向量模型是以信息熵理论为基础,引入Theil不均衡指数,按照评价数据的离散程度来确定各评价指标的权重。

    Based on the entropy fundamentals , Theil index and the method of the best solution model of optimal membership degree vector were introduced .

  22. 并且使用信息熵、回归分析和SP表分析的应用案例详细解释了如何使用本系统进行教育信息处理方面的应用研究。

    And we make use of these cases such as Information Entropy , Hierarchical Cluster Analysis , SP Form Analysis and so on to define how to make research in educational information processing by using this system .

  23. 介绍了非线性科学中的分形维方法和信息熵方法,及其在房颤信息的处理和分析中的应用。设计了将归一化的P波曲线和f波曲线进行划分从而求出其格子维的方法。

    The fractal-dimension theory and the Shannon entropy theory of nonlinear science are briefly introduced , and the methods to apply them to analyzing the information of atrial fibrillation ( AF ) are developed for computing the grid-dimension values and the Shannon entropy values of P-wave and f-wave .

  24. 最大信息熵原理在波高分布中的应用结构方程模型参数估计的GME方法

    Application of Maximum Entropy Principle Method in Wave Height Distribution Generalized Maximum Entropy Method for Estimating Parameters of Structural Equation Model

  25. 简述了信息熵及熵最大原则。介绍了该原则在X射线分析中的几个应用(诸如,晶体结构测定,非晶态结构测定,织构分析,等等)。

    The information entropy and the maximum entropy principle are recounted briefly here some applications of this principle in X - ray analysis ( such as determination of the crystal structure , determination of the non - crystalline structure , texture analysis , etc. ) are introduced .

  26. 分别从系统能量和单机能量角度,在COI坐标和同步坐标下,利用信息熵法和PEBS法判断系统暂态稳定性。

    From system energy and single generator energy aspect , using information entropy function and PEBS analyzes transient stability of power system at COI and synchronism frame .

  27. 将TOPSIS模型应用于工程项目评标中,引用信息熵理论来计算各指标的权重,可以避免由专家确定权重的主观性。

    TOPSIS model is applied to the evaluation of project bid in the paper , the information entropy method is adopted in the calculation of parameter weight in order to avoid the subjectivism of fixing weight .

  28. 在粗糙集理论中,由于用模糊粗糙熵去度量RF集的不确定性更具有直观性,所以如何利用香农信息熵理论定义模糊粗糙集的熵的度量,是一个值得研究的问题。

    Using rough-fuzzy entropy to measure the uncertainty of RF set in the theory of rough set is much more intuitional . Therefore it is worthy of investigation of how the Shannon information theory is used to define the measurement of the entropy of rough-fuzzy set .

  29. 分析发现利用小波分析法算出的QRS波群能量占比及P波能量占比信息熵对健康人和心律不齐患者具有敏感性,可作为临床上诊断心律不齐患者的定量参考指标。

    Analysis shows that the energy proportion of the QRS complexes and information entropy of the P-wave energy proportion calculated by wavelet analysis are sensitive to the healthy and the arrhythmia patients , they can be used as a quantitative reference index for diagnose arrhythmia patients in clinic .

  30. 分析主流的SOM网络、GA、层次聚类、信息熵等主流聚类方法的特点,并基于这种结构模型,给出了相应离散化方法的应用要点。

    With the main clustering algorithm , SOM NN , GA , level clustering , information entropy as the typical examples , and based on the universal model , the algorithms ' characters are analyzed , also the corresponding executing main-points are presented .