scatter matrix 中文意思是什麼
scatter matrix
解釋
離差陣-
Gained same data with literature. paper based cascade scatter matrix field matching equation. program currency frame grating programme. obtain several design project of high power and high efficiency grating - circular polarization
分析了薄片型光柵圓極化器的傳輸特性和極化特性，數值計算的結果與文獻給出的實驗測得結果具有較好的一致。 -
By constructing weighted between - class scatter matrix, the classes that are closer to one another are likely to have a greater confusion and should be given a greater weightage
該演算法通過構建加權的類間散布矩陣，將距離較近的容易混淆的類別賦以較大的權值。 -
A concise representation method of between - class scatter matrix and population scatter matrix is proposed, which suits for all the applications of pattern recognition using fisher criteria
提出了散布矩陣的一種簡潔表示方法，這一簡潔表示方法適合於一切使用fisher鑒別準則的模式識別問題。 -
Standard face images are formed through the above - mentioned processing. during the feature extraction, for those standard face images, regarding the between - class scatter matrix as generating matrix, we extract the algebraic features of face images through k - l transform and singular value decomposition
在人臉特徵提取過程中，對經過預處理的標準人臉圖像，以類間散布矩陣為產生矩陣，通過k - l變換降維並結合奇異值分解來提取人臉代數特徵。 -
Just like that the core patch which is not adjacent to water and hilly woods has the flat edge, near round shape, high trees diversity and abundant native trees, which can reduce the external disturb and protect the native trees. in addition, the matrix in the landscape is the patch that is flat, not adjacent to water and scatter woods has low fragmentation degree, smooth edge and near ellipse shape, which is adapted to matrix
如，非鄰水山地密林團聚分佈，邊界平滑，呈圓形，樹種多樣性指數高，當地物種豐富，這種格局能顯著降低外部干擾，保護主要當地物種，與核心斑塊的功能相適應；非鄰水平地疏林斑塊邊界平滑，近橢圓形，這種格局有利於分散干擾危險，與本底斑塊的功能相適應。 -
While flda only can get one optimal discriminating vector, by maximizing the fisher criterion, due to that the rank of the between - class scatter matrix is at most 1 for binary - class problem
但類間離散度矩陣的秩最大隻能為1 ，決定了flda只能取一個判別方向（最大特徵值對應的特徵向量） ，無法利用其它方向的判別信息。 -
( 2 ) a series of new methods of feature extraction based on the optimal discriminant analysis are proposed, including the new lda algorithm based on the spectral decomposition of within - class scatter matrix sw which is effective when the number of class is small, an improved algorithm of optimal set of discriminant vectors based on the svd which is effective for face recognition, and the kernel fisher discriminant method ( kfdm ). experimental results on orl show that the kfdm outperforms conventional fisher discriminant methods in face recognition, however the computational load is much higher than those of conventional algorithms
（ 2 ）提出了基於最優鑒別分析的圖象特徵抽取的一系列新方法，它們包括：基於對類內矩陣s _ w進行譜分解的f - s最優鑒別矢量集方法，該方法在類別數比較小時非常有效；一種改進的基於svd的最優鑒別矢量求解演算法，將該方法用於人臉識別時有較好的性能；非線性最優鑒別矢量集方法，該方法雖然有效，但計算時間較長。 -
Terrain slope information can be drawn from polarimetric synthetic aperture radar ( sar ) two - dimensional image, so that three - dimensional image can be generated. it differs from two - pass or repeated trace insar that uses interference phase method to obtain topography height. the p - sar three - dimensional image technology uses the stokes matrix formed by two - dimensional images resolution cells, then applying polarimetric synthesize to stokes matrix can produce polarization signature of the scatter cross - section a - (, x ) for any ( ellipticity ) and ( orientation ) polarization state
這種方法不同於重復軌道和雙通道insar系統，不是利用干涉法提取高度信息，而是利用極化sar二維圖像各分辨單元的stokes矩陣，通過極化綜合估計每個分辨單元的共極化散射特性和交叉極化散射特性（極化指紋） ，以及共極化散射特性最大值時對應的極化橢圓度x利極化橢圓方向角，求解地形的高度輪廓。 -
Based on this idea, a general framework for linear analysis in singular case is developed, i. e., pca is first used to reduce the dimension of image space to m ( the rank of the total scatter matrix )
更為重要的是，我們進一步揭示了高維、小樣本情況下線性鑒別分析的本質，即先作k - l變換，再用fisher鑒別變換作二次特徵抽取。 -
Parametric estimation based on robust scatter matrix in semiparametric regression model
半參數回歸模型中基於穩健散布陣的參數估計 -
Hence, the transformation matrix composed with the eigenvectors corresponding to the largest eigenvalues of the transferred between - class scatter can maximize the fisher criteria
然後在這個零空間里，尋找對應于樣本類間離散度矩陣的較大特徵值的特徵向量作為最終降維的轉換矩陣。
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