最大似或然法 的英文怎麼說
中文拼音 [zuìdàsìhuòránfǎ]
最大似或然法
英文
maximum likelihood method-
Many of communication systems take the convolutional code and viterbi algorithm as the channel coding scheme. the viterbi algorithm decoding is a kind of maximum likelihood decoding, and its performance is good over additive white gaussian noise ( awgn ) channel, but when burst errors occur, the decoding performance may be greatly degraded
維特比譯碼演算法是最大似然譯碼，在由高斯白噪聲引起的隨機錯誤的通道中有良好的性能，但當通道錯誤集中或為突發錯誤通道時，維特比譯碼演算法則性能急劇下降。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
空間譜估計的演算法大致分兩大類:一是基於極大似然估計和最大后驗概率估計統計理論的演算法，包括:極大似然估計法（ ml ） 、最大熵法等;另一類是基於對協方差矩陣進行子空間分解或投影的演算法，包括:矢量特徵法、多重信號分類法（ music ） 、投影矩陣法等。其中， music法是一種經典的空間譜估計主流演算法，具有超強的分辨性能，但它無法實現對相干信號進行測向分辨。A new heuristic search method is devised for maximum likelihood method, which first constructs a starting tree, and then through branch swapping searches for trees best resembling the present optimal tree and locates a better tree. repeat this process, till no more better trees are generated or the upper iteration limit is arrived and the program ends
對最大似然法，改進了一種新的啟發式搜索:隨機建立一棵初始樹，然後通過查看與當前最優樹拓撲最近的樹，從中尋找更優樹，不斷地更新當前最優樹，直到無法找到更優樹或者達到了搜索次數的上限，演算法停止。At present, most of the estimation algorithms are implemented by the training sequence by which the characteristics of the sequence was known by the receiver. maximum likelihood estimation or the projection of training sequence is frequently used to estimate the snr. but these techniques will increase the complexity of the reciever
現在所提出的估計演算法大多數是基於發送訓練序列的方法，即傳送完全已知的信號序列，然後通過對此序列的接收和分析來估計通道參數，如利用訓練序列的最大似然估計，或利用其投影來估計通道參數的方法，但是這些利用訓練序列的估計方法都存在增加設備復雜度的缺點。The constraints described are a bit like one might find in a " random walk " algorithm, with the end condition resembling a " statisficing " or " local minimum " result - but certainly the requirements are simpler than most real - world ones
上述的約束有點象可以在「隨機遍歷」演算法找到的約束，結束條件類似「統計」或「局部最小值」結果但當然，這要比大多數現實世界中簡單。分享友人