covariance analysis 中文意思是什麼
covariance analysis
解釋
積差分析- covariance : n. 【統計學】協方差，協變性；共離散。
- analysis : n. （pl. -ses ）1. 分解，分析；【數學】解析。2. 梗概，要略。3. 〈美國〉用精神分析法治療（＝ psychoanalysis）。
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An algorithm of covariance analysis
協方差分析的一種演算法 -
By using the optimized covariance matrices to optimize the new regularized discriminant analysis ( rda ), the correct classification rate is higher than that by the old rda
利用優化的協方差矩陣對正則化判別分析方法進行優化，其模式分類正確率有顯著提高。 -
Covariance analysis with forward stepwise variable selection was carried out
統計方法採用逐步向前變量選擇協方差分析。 -
Backed up by the soplat theory based on particle kinematics, the second chapter of this paper presents with analysis and simulation of several single observer passive measurement models, which uses such relative movement parameters as bearings changing rates and centrifugal acceleration information on the basis of bearings measurements. in the third chapter, the observability of location respectively using bearings and its changing rates information and centrifugal acceleration information is analyzed, and its observable condition is got. the fourth chapter puts forward the modified covariance extended kalman filtering ( mvekf ) against the defect of traditional extended kalman filtering ( ekf ), whose performance is simultaneously compared in the chapter with the performance of ususal tracking algorithm such as ekf, mgekf, iekf by computer simulation
在近年來提出的基於質點運動學原理的單站無源定位理論基礎上，本文第二章提出了幾種在角度測量的基礎上增加角度變化率及相對運動的離心加速度等運動學參數的單站無源測量模型，並對它們進行了分析和模擬；第三章分別對利用角度及其變化率信息定位和利用離心加速度信息定位的可觀測性進行分析並得到了相應的可觀測條件；第四章針對傳統擴展卡爾曼（ ekf ）方法的缺點，提出了一種修正協方差的擴展卡爾曼濾波（ mvefk ）方法，並將其和ekf 、 mgekf 、 iekf等常用的單站無源定位濾波方法進行了性能模擬比較；第五章通過引入雷達機動目標跟蹤方法和模型，提出了利用角度及其變化率對機動輻射源跟蹤的多級噪聲自適應方法和imm方法；第六章主要對角度變化率和離心加速度參數的獲取技術進行了研究，提出了幾種高精度測量脈沖序列多普勒頻率變化率的方法。 -
Covariance analysis was used to analyze herbicide efficacy data from rapeseed experiments
摘要採用協方差分析方法，對油菜田除草劑的試驗結果進行了分析。 -
It should be found that in sphere coordinate system the solution covariance is stable and can be used to a simulation / covariance analysis
經過這種變換后，解算參數的協方差是穩定的，可進行模擬協方差分析。 -
The covariance analysis indicated that the difference was significant between the intercepts in the regression equations, but not between the slopes
協方差分析表明，各回歸方程的斜率（體重指數b ）之間差異不顯著，截距a值差異極顯著。 -
The concise and unified formula for testing any local parameter using f - statistic in covariance analysis is presented. the specific algorithm is also described
給出了在協方差分析中，對任何局部參數進行檢驗時使用f -統計量的簡明統一表達式，也給出了具體的演算法 -
When compared with single factor analysis of variance, covariance analysis reduced efficacy evaluation error resulting from uneven weed distribution in the field
結果表明，與按單因素試驗方差分析相比，協方差分析方法可以減小因雜草田間分佈不均勻而導致的調查誤差。 -
Here the methods of covariance analysis and vibration analysis are employed to obtain the background and resonant component of wind - induced response. and the methods of load - response - correlation and inertial force are used to obtain the background and resonant component of eswl
對于風致響應的背景分量和共振分量，分別採用方差分析法和振動分析方法來求解；對于等效風荷載的背景分量和共振分量，分別採用lrc法和慣性力法來求解。 -
There was double - logarithmic linear correlation significantly between specific weight metabolic rate and temperature in each of weight groups. temperature exponent ( b ) in the regression equation increased with weight increasing. the covariance analysis showed that the difference between the every two temperature exponents in the equations was significant
（ 2 ）特定體重代謝率隨溫度的上升而上升，各體重組的代謝率與溫度之間均呈顯著的雙對數直線相關；溫度指數（ b ）隨體重的增加呈現上升的趨勢，協方差分析表明，回歸方程的溫度指數（ b ）間差異顯著。 -
In this thesis, based on principal component analysis ( pca ), covariance stationary processes and spectral analysis theory of linear operator, spectral principal component analysis ( spca ) is put forward
在主成分分析的基礎上，基於協方差平穩過程理論和線性運算元譜分析理論，本文提出了譜主成分分析。 -
Analysis of covariance structures by quasi - likelihood with dual geometrical approach
協方差結構分析中擬似然估計的對偶幾何方法 -
Conclusion modeling the covariance structure is especially important for analysis of repeated measures data because measurements taken close in time are potentially more highly correlated than those taken far apart in time
結論由於在重復測量資料中，同一受試者的不同觀測值之間具有相關性特點，故對其指定協方差結構尤其重要。 -
The conventional principal component analysis ( pca ) and fisher linear discriminant analysis ( lda ) are based on vectors. that is to say, if we use them to deal with the image recognition problem, the first step is to transform original image matrices into same dimensional vectors, and then rely on these vectors to evaluate the covariance matrix and to determine the projector
所提出的這兩種方法的共同特點是，在進行圖像特徵抽取時，不需要事先將圖像矩陣轉化為高維的圖像向量，而是直接利用圖像矩陣本身構造圖像散布矩陣，然後基於這些散布矩陣進行主分量分析與線性鑒別分析。 -
The final results obtained in this paper contained that the optimal interpolation scheme highlighted by the covariance that the correlation between different time and the correlation between different place being considered ; that the simplification of kalman filter with the singular - value decomposition ( svd ) and the direct construction of state transition matrix pfeceded with " inverse vector expression " ; and that the analysis of t / p data and its blending with theoretical model
這些成果包括：建立考慮了時間相關的方差矩陣和時空相關的最優插值演算法；對卡爾曼濾波演算法進行了svd簡化以及建立了顯式的狀態轉移矩陣；將t p實時衛星數據進行調和分析並與數值模型進行同化處理。 -
Furthermore, utilizing the characteristic that filtering error covariance expresses filtering precision and the principle of information conservation, the dynamic and reasonable distribution of distributed tracks weight coefficient is accomplished. jerk model and strong tracking filter is organically assembled, and based on spatio - temporal synthetically analysis and lme, a self - learning estimation method of the system measurement variance is given. the method improves obviously the
3 、將jerk模型與強跟蹤濾波演算法有機地結合，並利用時空綜合分析和極大似然估計的思想推導出了一種系統量測方差自學習修正方法，以優化強跟蹤濾波演算法中次優漸消因子和濾波增益的在線選擇，同時根據多傳感器數據融合具有改善濾波精度的性質，進而給出一種基於jerk模型的多傳感器數據融合演算法。 -
First, the thesis introduces the definitions and the attributes of the higher - order statistics. it is insensitive to additive gaussian noise ( white or colored ), which is what we base on to doa problems. then two doa estimation algorithms based on higher - order statistics are presented, one is that forming cumulant matrix pencil used in esprit to estimate doa problems, the other is spectrum estimation method for doa estimation based on the eigenstructure analysis of the fourth - order cumulant, and comparing the effects of the estimation to conventional covariance - based doa algorithms "
論文首先對高階統計量的定義和性質作了介紹，特別指出了高階統計量對加性高斯噪聲（白色或有色）不敏感，這是我們利用它進行波達方向估計的理論依據，然後文中提出了兩種基於高階統計量的波達方向估計方法，一種是利用子空間旋轉不變技術構造四階累積量矩陣進行估計的方法，另一種是基於四階累積量陣特徵分解的空間譜估計測向方法，並將它們的估計效果與傳統協方差方法的效果進行比較。 -
The t - test and one - way multi - analysis of covariance were used where appropriate
研究所得資料，以獨立樣本t考驗、單因子多變項共變數分析進行分析。 -
Statistical inference for nonparametric analysis of covariance via varying coefficient models
非參數協方差分析基於變系數模型的統計推斷
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