training sequence 中文意思是什麼
training sequence
解釋
訓練序列-
At first, the text is segmented to words and converted to a sequence of part - of - speech tags ; then based on the pos tags sequence parameters and phrase - break distance information from training, markov model is used to get the most likely phrase break sequence
首先，文本進行分詞，並轉換為一列由詞性標記所組成的序列；然後使用馬爾可夫模型，利用人工標注數據庫訓練詞語連接處詞性標注序列的概率分佈和連接類型序列的距離信息，得到輸入的詞性標記序列對應的具有最大似然概率的連接類型序列，最後利用后處理規則進行適當的糾錯。 -
Blind equalization ( be ) needs no training sequence, which means higher data rate
而盲均衡演算法不需要訓練序列，可有效地提高信息的傳輸速率。 -
Secondly, it was. made theoretical analyses about the optimal training sequence design by the maximum likelihood estimation method and obtained the corresponding results, which were compared with the separate results derived by the minimum mean square error ( mmse ) estimation method in the other literature. at last, it was analyzed the impac
其次進行了採用最大似然（ ml ）估計法的最佳訓練序列設計的理論分析，分別得到了有關結果，並和其他文獻中採用最小均方誤差（ mmse ）估計法的設計結果進行了分析比較，得到了有關結論。 -
Blind equalization techniques rely on solely the received channel output signal to adjust the equalizer weights without a known training sequence available
盲均衡就是不藉助于訓練序列而僅僅利用接收序列就實現均衡的一種新興的均衡技術。 -
But the frequent use of training sequence is certainly a waste of channel bandwidth. research shows that with the prior knowledge of only the signature waveform and timing of the user of interest, blind adaptive multiuser detector can effectively detect data symbol of the desired user without training data sequence for every active user
在傳統多用戶檢測技術基礎上，自適應多用戶檢測利用訓練序列在僅知道期望用戶地址pn碼及其定時信息條件下就可以進行檢測，不足的就是訓練序列佔用了額外的頻率資源。 -
Periodic training sequence is essential for the conventional adaptive equalizers to combat the isi, but it wastes plenty of bandwidth
採用傳統的自適應均衡技術抑制碼間干擾，需要重復發送訓練序列，佔用大量本不富裕的帶寬。 -
According to the utilized face database, three facial expression categories are defined : neutral, happiness and anger. the categorization architecture is based on a som. in order to eliminate influence of initial values and sequence of input examples in som, supervised learning is introduced into the training stage
分類器的設計採用的是基於自組織神經網路的方法，為了克服傳統的自組織映射神經網路的訓練結果容易受訓練樣本的輸入順序和權值初值影響，而導致訓練結果不符合期望的問題，因此，在訓練過程中引入了監督機制，以使訓練結果與期望相符。 -
All of these make the new teaching materials more agile and practicable. in content structure, above all, the two series of teaching materials are consistent with each other in knowledge structure, while the new ones increase and delete some knowledge points, which make the backbone stand out and the arrangement evident ; the structure of the new materials run reasonably through adjusting the sequence of certain paragraphs ; secondly, in capability structure, compared with the old ones, the new teaching material enhance the ability - trained degree, which acclimate the demand of eqo education ; thirdly, in deal - educated structure, the new teaching materials enlarge the connotation of idea quality training, instruct students in various ways, enhance the teaching materials educational value. in a word, the new teaching materials make a great progress in structure than the old ones
從實質結構看，首先，在知識結構上，新教材與舊教材的知識體系大體保持一致，但是新教材通過增刪許多知識點，使教學內容主幹突出、層次分明，並更加貼近生活、聯系社會；通過調整某些章節的編排順序，使「三序」更好地結合起來；其次，在能力結構上，與舊教材相比，新教材分別在課文系統、實驗系統、練習系統中加大了能力培養的力度，順應了當前素質教育對學生提出的要求；最後，在思想品質上的培養方面，新教材擴展了思想品質培養的內涵，從多方面入手，採用多種方式教育學生，增強了教材的思想價值 -
Training sequence code
訓練序列碼 -
In this case, blind equalization techniques which need not any training sequence are preferred for underwater acoustic communication
因此，對於水聲通信通道，人們更傾向于採用不需要發送訓練序列的盲均衡技術。 -
The conventional equalizer resort to a training sequence in order to overcome inter - symbol interference. but this method would influence communication efficiency
傳統均衡器克服isi的方法是發送訓練序列，但是這會影響通信的效率。 -
In this paper, we discuss the principle of mimo - ofdm system based on the introduction of fading channels. furthermore, the channel estimation technique in mimo - ofdm system is investigated, with the emphasis on training sequence - based and pilot - based channel estimation methods, and also several basic and improved algorithms are given respectively. finally, the analysis and comparison of these algorithms is made by computer simulation
本文在分析移動無線通道衰落特性的基礎上，闡述了mimo - ofdm系統的基本原理，並圍繞該系統中通道估計這一關鍵技術，深入研究了基於訓練序列和基於導頻符號的兩類通道估計方法，給出幾種相應的通道估計演算法以及它們的改進演算法，最後結合matlab模擬對這些演算法的有效性和可行性進行了全面地分析與比較。 -
In the patent document, a training sequence is designed to estimate the parameters in pcma. but in this article will do some researcher in the parameters estimate without training. because of the lack of references, the estimate works are very hard
在pcma中，參數估計很重要，專利中為了快速得到各個參數的估計值，是通過兩個發送終端輪流抑制自信號，讓對方發送訓練序列來對各個參數進行估計的。 -
A new joint timing and frequency synchronization method for ofdm based on short training sequence
一種新的基於區域的圖像相似性計算 -
In addition, sometimes it is impossible to transmit training sequence. however blind equalization technique can depend on only the received data sequence to equalize the channels
而盲均衡技術可以不用藉助訓練序列，僅僅根據接收到的信息序列對通道進行自適應均衡，因而引起廣泛研究。 -
In training process, we use kernel - based fisher discrimination analysis ( kfda ) method to train the input sample vectors. the method has been used in face recognition and has been demonstrated better recognition capability than other methods ( pca, kpca, svm ). we calculate the optimal subspace wopt and project the sample gait sequences to wopt, then get the tracks of the sequences, calculate the track centroid and calculate the exemplar projection centroid of the sequences in the same class, and the exemplar projection centroid represents the class template. to test the class of a gait sequence, we also project the test sequence to the eigenspace, and calculate the track centroid, then calculate the euclidean distance of the test sequence tracking centroid with the sample sequences ’ exemplar projection centroids. and the class which the test sequence belongs to is the one that the sample sequence which the euclidean distance is shortest belongs to
該方法在人臉識別的研究中已有採用並在同樣測試條件下取得比其他識別方法更好的識別性能。採用kfda方法取得最優特徵空間wopt ，把步態樣本序列映射到wopt中，取得樣本序列在特徵空間中的軌跡，計算軌跡質心，把同類樣本序列的軌跡質心進行平均求得該類的標本投影軌跡質心，作為該類的模板。在識別時，將測試序列也投影到特徵空間中，取得序列軌跡質心，對測試序列軌跡質心與樣本的標本投影軌跡質心計算它們的歐氏距離。 -
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。 -
Furthermore, this paper exploringly studies an 802. 1 la high - speed wlan with the 54mbps data rate, and presents a sort of time synchronization and frequency offset estimation method based on the frequency domain auto - correlation of the unique preamble training sequence of 802. 11 plcp frame ; the method have the high time precision, the wide frequency estimat ion range and short convergence process ; and moreover, it can applied to other frame communication system
另外本文還對最高傳輸速率為54mbps的802 . 11a高速無線局域網系統進行了探索性研究，討論了ofdm調制技術在無線局域網中的應用；結合802 . 11a物理層數據幀結構特點，提出了一種基於前導訓練符號序列的頻域自相關時間和頻率同步方法，此方法具有定時精度高、頻偏估計范圍寬和同步建立迅速等特點，也適合於其它幀通信應用場合。 -
Blind equalization technology is a very popular research topic because it can adaptively equalize without training sequence. blind equalization algorithm based on hos ( higher - order statistics ) was presented and developed in 80 ' s
基於高階統計量的盲均衡演算法在80年代末出現並得到發展，由於高階譜不僅含有信號的幅度信息，而且還含有相位特徵。 -
Some related res ults have been acquired after comparing these cdf with the theoretical capacity. in the fourth chapter, it was at first estimated all the channel coefficients by maximum likelihood estimation and minimum mean square error estimation method on the basis of the construction of the transmission frame and the mathematical model for the wireless mtmo system of channel estimation with training sequence
第四章首先基於訓練序列估計的無線mimo傳輸幀結構和數學模型，分別使用最小均方誤差估計法和最大似然估計法估計出了通道的各個系數，在小信噪比和大信噪比時，比較了兩種估計方法的估計誤差的方差。
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