log likelihood中文什么意思

發(fā)音:

用"log likelihood"造句

對數(shù)可能性

log: LOG, log ＝ logarithum.
likelihood: n. 1.可能(性)。 2.【數(shù)、統(tǒng)】似然，似真。 3. ...
conditional log likelihood function: 條件對數(shù)似然函數(shù)
log likelihood function: 對數(shù)概似函數(shù)
minus log likelihood ratio: 負對數(shù)似然比

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例句與用法

Log likelihood ratio decoding of ldpc coded modulation in ofdm system
編碼調(diào)制的對數(shù)似然比譯碼
Log likelihood function
對數(shù)概似函數(shù)
In chapter l , we introduce the relative background on this paper and give some simple expressions of the work which have been studied . in chapter 2 , in virtue of the notion of likelihood ratio the limit properties of the sequences of dependent nonnegative continuous random variables are studied , and a class of strong limit theorems represented by inequalities are obtained . the bounds given by these theorems depend on positive constant c . in chapter 3 , by means of the notion of log likelihood ratio , a kind random strong deviation theorem are obtained , and the bounds given by these theorems depend on r ( )
第一章，介紹本論文的選題背景，對已有的工作進行扼要的介紹；第二章，利用似然比的概念研究相依連續(xù)型非負隨機變量序列的極限性質(zhì)，得到一類強偏差定理，其偏差界依賴于正常數(shù)c ；第三章，利用對數(shù)似然比的概念得到一類隨機偏差定理，其偏差界依賴于r ( ) ，證明中引進了尾概率和尾概率的laplace變換的概念；第四章，利用對數(shù)似然比的概念，得到了一類關(guān)于任意連續(xù)型隨機變量序列的泛函的強偏差定理。
In this paper , by means of the notion of likelihood ratio and log likelihood ratio the limit properties of the sequences of dependent continuous random variables are studied , and a class of strong limit theorems represented by inequalities are obtained . in the proof an approach of applying the tool of laplace transform to the study of strong limit theorem is proposed
本論文繼續(xù)這方面的工作，利用似然比、對數(shù)似然比的概念研究相依連續(xù)型隨機變量序列的極限性質(zhì)，得到相應(yīng)的用不等式表示的強偏差定理。證明中提出了將laplace變換的工具應(yīng)用于強極限定理研究的一種方法。
In chapter 4 , the purpose of this chapter is to establish a kind of strong deviation theorems of functional for the sequences of arbitrary continuous random variables , by using the conception of log likelihood ratio , and extend the strong deviation theorems on the differential entropy for dependent arbitrary continuous information sources on the the probability space ( , . f , p )
使得對于在概率空間( ， f ， p )上的任意連續(xù)型信源的微分熵的強偏差定理是本文的推論；第五章，總結(jié)本文的主要結(jié)論。