例句與造句

1. Maximum entropy method for nonlinear l1 problem
   1問題的極大熵方法
2. Maximum entropy method for linear programming with bounded variables
   變量有界線性規(guī)劃的極大熵方法
3. Maximum entropy method and quadratic programming sub - problem ' s explicit solution
   極大熵方法與二次規(guī)劃子問題的顯式解
4. In this thesis the basic principle of maximum entropy method ( mem ) and its applications in image restoration are thoroughly discussed
   最大熵方法是一種非線性的圖像恢復(fù)方法，過去的研究主要圍繞天文圖像的處理而進(jìn)行。
5. A context - dependent polyphone disambiguation technology was proposed , combined with the decision tree and maximum entropy methods , the accuracy can be improved to 99 . 82 %
   采取結(jié)合上下文信息及語法信息的多音字消歧技術(shù)，利用決策樹和最大熵等模式識別方法，使注音正確率達(dá)到99 . 82 % 。
6. It's difficult to find maximum entropy method in a sentence. 用maximum entropy method造句挺難的
7. According to the maximum entropy method , a program applied to compute reliability of cwr dynamic stability is worked out and put into practice to analyze reliability of cwr dynamic stability , getting the safety allowable temperature under design reliability index
   根據(jù)反應(yīng)極值最大熵擬合法編制了無縫線路動力穩(wěn)定性可靠度計算程序，分析了高速鐵路無縫線路動力穩(wěn)定性的可靠度，得到滿足目標(biāo)可靠指標(biāo)的允許溫升。
8. Maximum entropy method is an effective smoothing one for the finite min - max problem , which , by adding shannon ' s informational entropy as a regularizing term to the lagrangian function of min - max problem , yields a smooth function that uniformly approaches the non - smooth max - valued function
   極大熵方法是解有限極大極小問題的一種有效光滑化法，它通過在極大極小問題的拉格朗日函數(shù)上引進(jìn)shannon信息熵作正則項，給出一致逼近極大值函數(shù)的光滑函數(shù)。
9. The second chapter reveals the mathematical essence of entropy regularization method for the finite min - max problem , through exploring the relationship between entropy regularization method and exponential penalty function method . the third chapter extends maximum entropy method to a general inequality constrained optimization problem and establishes the lagrangian regularization approach . the fourth chapter presents a unified framework for constructing penalty functions by virtue of the lagrangian regularization approach , and illustrates it by some specific penalty and barrier function examples
   第一章為緒論，簡單描述了熵正則化方法與罰函數(shù)法的研究現(xiàn)狀；第二章，針對有限極大極小問題，通過研究熵正則化方法與指數(shù)(乘子)罰函數(shù)方法之間的關(guān)系，揭示熵正則方法的數(shù)學(xué)本質(zhì)；第三章將極大熵方法推廣到一般不等式約束優(yōu)化問題上，建立了拉格朗日正則化方法；第四章利用第三章建立的拉格朗日正則化方法，給出一種構(gòu)造罰函數(shù)的統(tǒng)一框架，并通過具體的罰和障礙函數(shù)例子加以說明。
10. Further , some knowledge of information theory are introduced to describe the regularity of process system calls such as the sequential dependency relationship between neighboring system calls . the use of information theory provides theoretic proof for creating more effective detecting models . in the end , applying for the maximum entropy method in information theory , a maximum entropy model of intrusion detection is presented
    同時，為了提高入侵檢測的準(zhǔn)確性，又在原有的馬爾可夫鏈模型的基礎(chǔ)上，引進(jìn)信息理論中的信息熵，條件熵等概念來更好地刻畫進(jìn)程系統(tǒng)調(diào)用序列的時序依賴關(guān)系，從而為建立更好的檢測模型提供信息理論依據(jù)。
11. There are mainly two type of algorithms used for spatial spectrum estimation : one is those based on bayesian maximum likelihood method , like the ml ( maximum likelihood ) algorithm , maximum entropy method and etc . , the others are based on the spatial decomposition or projection of correlation matrix , this kind of algorithm include vector characterization method , music ( multiple signal classification ) algorithm , projection matrix method , etc . music is a classical spatial spectrum estimation algorithm that has a super high resolution and is widely used today , however , it cannot estimate doa of signals that are correlated
    空間譜估計的算法大致分兩大類:一是基于極大似然估計和最大后驗概率估計統(tǒng)計理論的算法,包括:極大似然估計法( ml ) 、最大熵法等;另一類是基于對協(xié)方差矩陣進(jìn)行子空間分解或投影的算法,包括:矢量特征法、多重信號分類法( music ) 、投影矩陣法等。其中, music法是一種經(jīng)典的空間譜估計主流算法,具有超強(qiáng)的分辨性能,但它無法實現(xiàn)對相干信號進(jìn)行測向分辨。