least-squares estimation 中文意思是什麼

least-squares estimation 解釋
最玄乘估計
  • least : adj （little 的最高級，比較級為 less 或 lesser）1 最小的，最少的 （opp most）。2 最不重要的，地位...
  • squares : 方鋼
  • estimation : n. 1. 估計，評價。2. 預算，預算額；概算。3. 尊重，尊敬。4. 意見，判斷。5. 【化學】估定；測定。
  1. Then discusses its properties, such as biased property, relative efficiency of generalized variance and superiority comparisons between generalized ridge estimation and generalized least squares estimation. shows iterative algorithm based on the mean dispersion error

    該估計雖然具有偏崎，但其估計精度具有良好的性質，如：有偏性、方差一致最優性、相對于廣義最小二乘估計的廣義方差效率、 mde ? ?有效性等。
  2. We make the following assumption for when 2 is positive definite matrix, different estimators about matrix of regression coefficients and inefficiency of least squares estimate have been discussed in many documents. considered 2 is nonnegative definite matrix, this thesis derives best linear unbiased estimate of parameter matrix b and estimable parameter function kbl under the meaning of matrix nonnegative definite and the property of maximum probability of blue is investigated. next, we discuss some necessary and sufficient conditions of the equality of the lse and blue, then we derive the estimation of the deviation bet - ween the least squares and the best linear unbias estimators of the mean matrix, meanwhile a relative efficiency of lse ofb is proposed and its bound is given

    當0時，眾多文獻討論了回歸系數陣的各種估計及lse的有效性，本文考慮了當0的情形，給出了回歸系數陣b及其可估參數函數kbl的在矩陣非負定意義下的最優估計（ blue ） ，研究了它的一個最大概率性質，並且討論了最小二乘估計成為最佳線性無偏估計的充分必要條件，在此基礎上給出了均值矩陣的最小二乘估計與blue的偏差估計，定義了lse相對于blue的一個相對效率，並給出了它的界。
  3. Based on the least squares and biased estimation especially ridge estimation, a new estimation, that is, generalized ridge estimation is put forward through studies on restriction of the parameter. model ' s prediction being considered, comparison of superiority of optimal and classical predictions with respect to the ridge estimation is showed. regression diagnoses especially distance for principal components estimation is discussed

    論文基於最小二乘估計及有偏估計特別是嶺估計，對參數的約束條件做了進一步研究，並提出一種新型估計即廣義嶺型估計；對模型的點預測問題進行深入探索，得出一種基於嶺估計關于經典預測和最優預測的最優性判別條件；也對回歸診斷特別是基於主成分估計的距離進行了深入探討。
  4. 2 ) systematically introduced parameter estimation of distributed sources on the base of models, including the maximum likelihood estimate, least squares estimator, dspe, dispare, etc. 3 ) studied four low complexity algorithms : one order approximation, two point sources approximation, traditional beamforming and relax of parameter estimation

    2 ）在模型基礎上系統地介紹了已有分散式目標參數估計方法，包括最大似然與最小二乘演算法， dspe和dispare演算法等。 3 ）研究了四種低復雜度演算法：一階近似演算法、兩點近似的演算法、常規波束形成演算法和relax演算法，這些演算法都是次優演算法，但計算量小，具有實用價值。
  5. The new algorithm starts from an initial estimate which is based on the hough transform, and a rectangular window is centered using the current line approximation, and a new line estimation is generated by making a total least squares fit through the pixels contained within the window. this is repeated until convergence is reached. lastly, we have suggested a new technique which may recover the motion and structure parameters of a moving object by using of 21 optical flow lines based on the optical flow fields of the feature line this thesis is the project supported by aeronautical foundation science ( no. 99f53065 ) and research center of measuring and testing technologies, and control engineering in nanchang institute of aeronautical technology ( no. 2001 - 15 )

    演算法的思路是：首先，在小區域內運用霍夫變換確定直線的初始值；其次，以直線的初始值所對應的直線為中心線，建立一個矩形框；最後，利用矩形框內所包含的邊緣點數據不斷地迭代直至收斂，從而達到進一步修正直線的坐標參數；本文基於特徵直線的光流場，即線流場，建立了一種利用21條光流線確定空間三維物體旋轉運動參數、平移運動參數以及對應的空間直線坐標的線性演算法。
  6. Two - stage algorithms of parameter estimation for the autoregressive moving average ( arma ) models are presented, which are called two - stage recursive least squares algorithm ( 2 - rls ) and recursive least squares - pseudoinverse algorithm ( rls - pi )

    本文提出了自回歸滑動平均（ arma ）模型的兩段參數估計演算法：兩段遞推最小二乘演算法（ 2 - rls ）和遞推最小二乘-偽逆演算法（ rls - pi ） 。
  7. The first chapter quotes three methods for determining the steady - state equivalent circuit parameters of an induction machine. they are the classical locked - rotor and no - load tests, the direct modification method and the recursive least - squares method. then a new parameter estimation method based on genetic algorithms is presented

    緒論首先引述了確定感應電動機穩態模型參數的其他三種方法：傳統的空載和堵轉試驗方法、直接修正參數法和遞推最小二乘法，並由此提出基於遺傳演算法的參數識別技術。
  8. Further, based on the method of pre - elimination of parameters, the formulae of the partly - weigthed least squares estimation with constraints on parts of the parameters are derived to include a prior information

    在顧及電離層加權模型的情況下，利用參數消去法，推導了加權最小二乘法估計模糊度實數解的公式。
  9. Some linear approaches reported recently without postprocessing to fir system identification are discussed. this paper improves the question of the promulgation of error due to estimating middle parameter frequently in other related methods, and presents a direct algorithm of estimating parameter without estimating middle coefficient. through proper mathematic means, for example, singular value decomposition ( svd ) or total - least squares solution ( tls ), this algorithm smoothes the noise and improves effectively the estimation performance

    和2階統計量相比，高階統計量不僅能夠有效抑制高斯有色噪聲的影響，而且能夠揭示隨機過程的相位特性，因此，高階統計量是解決非高斯、非最小相位、非因果系統和有色高斯噪聲環境的系統辨識和處理問題的重要分析工具。
  10. The results show that the ionosphere - weighted model or the tropospheric estimation, integrated with the partly - weigthed least squares, can improve, the success rate and the reliability of ambiguity resolution ; however, if the ionospheric delay or the tropospheric delay, which is modeled on random walk process or first - order gauss - markov process, is estimated with the kalman filter, it will reduce the success rate and the reliability of ambiguity resolution

    將電離層延遲作為零均值的隨機遊走過程（電離層加權模型） ，將對流層延遲作為靜態參數，採用非遞推形式的加權最小二乘法來估計，可以提高模糊度解算的成功率和可靠性。
  11. Ridge regression analysis is modified least - squares estimation. it can offer a stable forecasting when there is strong correlation between variables

    嶺回歸分析是一種修正的最小二乘估計法，當自變量系統中存在多重相關性時，它可以提供一個更為穩定的預測。
  12. A comparision between the partly - weigthed least - squares estimation and the kalman filter is made on precise kinematic gps positioning with the fixed ambiguities, which shows that the positioning results from the partly - weigthed least squares, which accuracy is at the level of 10 cm, are much more accurate than the results from the kalman filter, which accuracy is at the level of a few meters

    針對高精度動態定位結果的精度，對最小二乘法和經典kalman濾波這兩種演算法進行了綜合分析和比較。算例顯示，在高精度gps動態測量中，最小二乘法可以提供厘米級精度的位置結果，而kalman濾波演算法不但不能提高定位結果的精度，反而會給定位結果引入米級的偏差。
  13. The main research contents include : study the modeling and measure of tendency of customer group ' s requirements. use the method of least - squares estimation in conjoint analysis to model and measure the tendency of customer group ' s requirements and transform the fuzzy requirements of customer group into numerical attribute importance and level utility. solve the problems of estimation and optimization of regression model

    研究的主要內容包括：研究了客戶群體需求傾向的建模和量化過程：應用聯合分析法的最小二乘回歸模型建模和量化客戶群體需求傾向，將模糊的客戶群體需求傾向轉化為量化的屬性重要度和水平效應值，並解決了模型的有效性評估和優化問題。
  14. Compared with classical recursive extended least squares, their accuracy obviously is improved. applying these new algorithms to the parameter estimation problem for systems with measurement noises, some new approaches and algorithms of parameter estimation for system with measurement noises, are presented, for example, two - stage rels - gevers - wouters algorithm and three - stage rls - pi - gevers - wouters algorithm, which solve the biased parameter estimation problem by classical least squares method

    並將這些演算法推廣到帶觀測噪聲系統參數估計的問題，給出了帶觀測噪聲系統參數估計的一些新方法和新演算法，其中包括兩段rels - gevers - wouters演算法和三段rls - pi - gevers - wouters演算法，解決了用普通最小二乘法估計帶觀測噪聲系統未知參數的有偏問題。
  15. Based on the classical least squares method ( rls ) in system identification, the several new identification algorithms of parameter estimation for the autoregressive moving average ( arma ) model, are presented. they include univariable and multivariable two - stage recursive least squares - recursive extended least squares ( rls - rels ) and two - stage recursive least squares - pseudo - inverse ( rls - pi ) algorithms

    本文在系統辨識經典的最小二乘法（ rls ）的基礎上，提出了自回歸滑動平均（ arma ）模型參數估計的一些新的辨識演算法，它包括單變量和多變量兩段遞推最小二乘?遞推增廣最小二乘（ rls ? rels ）演算法和兩段遞推最小二乘?偽逆（ rls ? pi ）演算法等。
  16. Inefficiency of the least squares estimation in singular growth curve model

    奇異增長曲線模型中最小二乘估計的有效性
  17. A restricted least squares estimation for fuzzy linear regression models

    模糊線性回歸模型的約束最小二乘估計
  18. Sequential least squares estimation

    序貫最小二乘估計
  19. Universal penalized least squares estimation for semiparametric regression models

    半參數回歸模型的泛補償最小二乘估計
  20. Least squares estimation

    最小均方估計
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