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熵密度 meaning in Chinese

entropy density

Examples

  1. The entropy density is constant ahead of the shock .
    冲击波前方的熵密度是恒定的。
  2. For any information source on a countable set , the limit properties of relative likelihood ratio and log - likelihood ratio of entropy with respect to the independent geometry distribution , an important problem in the information theory is discussed
    摘要对任意的可列集上的信息源,探讨资讯论的一个重要问题,即探讨了相对于独立型几何分布的熵密度似然比与对数似然比的极限性质。
  3. More general quadratic constraints and entropy constrains of the density programming will be dealt with in this article . the two problems are widely applied in information theory , statistical mechanics , insurance business and game theory
    本文讨论比mdi问题更普遍的带有二次约束和熵密度约束的广义熵密度规划问题,这两类问题在信息论、统计力学、对策论和保险业中有着广泛的应用。
  4. The strong deviation theorems are new type theorems established by using the notion of the likelihood ratio . professor liu wen frist applied an analysis method in solving a class of strong deviation theorems for a sequense of random variables . later professor liu wen studied the shannon - mcmillan theorem in information theorems [ 2 ] - [ 8 ] and deviation theorems of non - negative continuous random variables [ 10 ] - [ 11 ] by using the analytic technique and obtained some strong deviation theorems . the chapter 2 of the paper studied a class of strong deviation theorems of function of two variables of information sources and obtained a further study of shannon - mcmillan theorem of markov information sourses by definning the using concept of entropy density divergence . the chapter 3 of the paper studied a class of strong deviation theorems of non - negative continuous random variables by using tool of transformation of laplace . information theory , as a branch of applied probability theory , becomes more and more important in appling
    刘文教授在解决大数定律中,用首创的分析方法得到一类随机变量序列的强偏差定理。后来,刘文教授把分析方法用于信息论中shannon - mcmillan定理和连续型随机变量的偏差定理的研究,得到了若干强偏差定理。本文的第二章是引进任意信源相对熵密度偏差的概念,并利用这个概念研究任意信源二元函数的一类强偏差定理,得到了马氏信源shannon - mcmillan定理的一个推广。

Related Words

  1. 熵平衡
  2. 振动熵
  3. 反应熵
  4. 熵产生
  5. 环境熵
  6. 零点熵
  7. 代码熵
  8. 形成熵
  9. 转动熵
  10. 熵弹簧
  11. 熵流
  12. 熵率
  13. 熵判别
  14. 熵判据
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