data sequence造句
例句與造句
- This makes it efficient and easy to page over large data sequences
這使得對(duì)大的數(shù)據(jù)表進(jìn)行分頁變得高效和容易。 - Because that way we can find repeating bytes , the most likely thing to repeat in a long data sequence
因?yàn)樵谝粋€(gè)很長(zhǎng)的數(shù)據(jù)序列中，最容易重復(fù)出現(xiàn)的就是字節(jié)。 - This paper increases the accuracy of gm model by smoothing the original data sequence in order to improve gm model
摘要用提高原始數(shù)據(jù)列光滑度的方法來提高gm模型的精度，從而改進(jìn)灰色模型。 - This article deals with many modeling methods of dynamic data sequence and compares the advantages and disadvantages of these methods
本論文首先研究了國(guó)內(nèi)外多種關(guān)于動(dòng)態(tài)數(shù)據(jù)序列建模方法，比較了各種方法的優(yōu)缺點(diǎn)。 - 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(shù)可以不用借助訓(xùn)練序列，僅僅根據(jù)接收到的信息序列對(duì)信道進(jìn)行自適應(yīng)均衡，因而引起廣泛研究。 - It's difficult to find data sequence in a sentence. 用data sequence造句挺難的
- Markov chain is suitable for short - term forecast of great capacity sample data sequence , but gray system forecast method is suitable for medium - term forecast of few capacity sample data sequence
馬爾柯夫鏈適用于大樣本數(shù)據(jù)序列的短期預(yù)測(cè)，而灰色系統(tǒng)預(yù)測(cè)方法適用于小樣本數(shù)據(jù)的中期預(yù)測(cè)。 - ( 3 ) interleave technology is used to deal with group errors . the interleaver can break the data sequence , and weaken the pertinence of the data sequence before and after interleaved . so it reduced the harms made by burst errors
( 3 )交織技術(shù)主要作用是對(duì)付成群錯(cuò)誤，交織器把輸入數(shù)據(jù)的順序打亂，使得交織前后數(shù)據(jù)序列的相關(guān)性減弱，從而大大降低突發(fā)性錯(cuò)誤造成的危害。 - 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(tǒng)多用戶檢測(cè)技術(shù)基礎(chǔ)上，自適應(yīng)多用戶檢測(cè)利用訓(xùn)練序列在僅知道期望用戶地址pn碼及其定時(shí)信息條件下就可以進(jìn)行檢測(cè)，不足的就是訓(xùn)練序列占用了額外的頻率資源。 - This paper put forward the fundamental idea of gray statistical method and made some exploration on theory and practical application of gray principal component analysts and gray factor analysis , 1 the fundamental idea of gray statistical method the nature included in less - data sequence is called available nature
本文提出了灰色統(tǒng)計(jì)的基本思想，從灰色主成分分析和灰色因子分析兩方面進(jìn)行了理論和實(shí)證的探討與分析。 1灰色統(tǒng)計(jì)方法的基本思想由包含現(xiàn)實(shí)信息的少數(shù)據(jù)序列所表現(xiàn)的規(guī)律，稱為現(xiàn)實(shí)規(guī)律。 - ( 4 ) both multi regression model and generalized tank model have high precision in calibration stage , but sharply decrease in verification . beside that , the quantity of observed data is vital for these two models . so it is suggest that the models be not adopted when data sequence is less than 12 years
西安理工大學(xué)碩士學(xué)位論文( 4 )多元回歸模型和概化的水箱模型，在建模時(shí)精度較高，檢驗(yàn)時(shí)下滑，而且對(duì)資料系列長(zhǎng)度的要求比其它模型要多得多，在資料不足12年的情況，建議不要使用這兩個(gè)模型。 - On the base of many dynamic data sequences of oxygen content , advanced rational dynamical data modeling strategy is introduced , which is correlated with the analyzed method of regression , grey theory and time sequence to the modeling of killing oxygen by adding aluminum model and the method is adopted about the separation of certain and uncertain signal and corresponding parameter estimation and mathematical model is put forward
根據(jù)定氧加鋁工藝中鋼包含氧量因工況等因素有所不同，在觀察若干爐含氧觀測(cè)數(shù)據(jù)序列的基礎(chǔ)上，引入先進(jìn)合理的觀測(cè)數(shù)據(jù)建模策略，結(jié)合回歸分析、灰色理論和時(shí)間序列建模的思想，建立了定氧加鋁模型。 - The detailed works are as follows : the finding patterns problems in the time - series data sequence are described , and a new trend logic expression method is introduced , and its algorithm and experiment result of algorithm are given ; time - scries data are disposed , and using the arctg . slope of line as the sample of pattern recognition , so ignoring the aberrance of pattern in the classified . in addition , a new time - series pattern finding algorithm based on higher - order neural network is put forward
同時(shí)給出了本文的具體的工作，主要是：對(duì)在時(shí)序數(shù)據(jù)序列中發(fā)現(xiàn)模式問題進(jìn)行了描述，并介紹了一種新的趨勢(shì)邏輯表示方法，給出了其算法及算法的實(shí)驗(yàn)結(jié)果；對(duì)時(shí)序數(shù)據(jù)進(jìn)行處理，提出了利用線段的斜率反正切值作為模式識(shí)別的樣本，從而在分類時(shí)忽略模式的畸變；另外，還提出了一個(gè)新的基于高階神經(jīng)網(wǎng)絡(luò)的時(shí)序模式發(fā)現(xiàn)算法。 - This paper firstly introduces the primary contents of forecasting , summarizes common forecasting methods and means of both quality and quantity , discusses the theoretical and practical research evolvement of grey forecasting and evaluating , analyzes the pretreatment of fundamental data sequence according to the primary procedure of forecasting , specifies the contents of grey forecasting and evaluating theory , and then carries into execution the application research on the base of the science and technology index data of jiangsu province
本文介紹了預(yù)測(cè)理論的基本內(nèi)容，并對(duì)常用的定性定量預(yù)測(cè)方法和理論進(jìn)行了簡(jiǎn)要介紹，重點(diǎn)討論了灰色預(yù)測(cè)評(píng)價(jià)理論和實(shí)踐的研究進(jìn)展，進(jìn)而按照預(yù)測(cè)工作的基本程序分析了基礎(chǔ)數(shù)據(jù)序列的預(yù)處理方法，介紹了灰色預(yù)測(cè)評(píng)價(jià)理論的基本內(nèi)容，并結(jié)合江蘇省科技綜合實(shí)力體系的數(shù)據(jù)進(jìn)行了應(yīng)用研究。 - By processing the observed data sequences of target position using the fuzzy imm approach based on current statistics model , the proposed method integrates multiple filtering and predicted values of target state from different trackers using the adaptive weighting fusion approach based on total least - squares error rule , which improves the precision and robustness of tracking system
該方法在對(duì)各跟蹤器輸出的目標(biāo)位置測(cè)量值序列采用基于“當(dāng)前”統(tǒng)計(jì)模型的模糊交互多模方法進(jìn)行處理的基礎(chǔ)上，采用基于總均方誤差最小規(guī)則的自適應(yīng)加權(quán)融合方法對(duì)目標(biāo)狀態(tài)的多個(gè)濾波與預(yù)測(cè)值進(jìn)行綜合處理，較大程度上提高了系統(tǒng)的跟蹤精度與穩(wěn)定性。
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