negative matrix 中文意思是什麼
negative matrix
解釋
負矩陣-
Beryllium powders with the same particle size and various contents of beo were prepared by pre - sintering - acid washing processes initiatively and the influence of beo alone on o mys of beryllium was observed and some new results have been obtained - compared with the content of beo, the distribution of beo in beryllium has more critical influence on mys ; finely dispersed beo along the grain boundaries and in the matrix results in the dispersion strengthening of beryllium matrix and thereby the higher mys value ; on the contrary, the coarser beo particles clustering on the grain boundaries results in negative influence on o mys
開創性地用預燒結? ?酸洗工藝制備了相同粒度、不同beo含量的鈹粉，從而開展了beo含量單獨對鈹材_ （ mys ）影響的研究，得出一些新的結果：與beo含量相比， beo在鈹中的分佈狀態對_ （ mys ）的影響更大。沿晶界、晶內彌散分佈的較細小beo對基體鈹有彌散強化作用，使_ （ mys ）即較高；如果beo較粗大地成簇狀聚集在晶界，反而對_ （ mys ）有不良的影響。 -
Methods by defining the concept of expected value decision matrix ( based on the ideal solution or the negative - ideal solution ), using the preference information on alternatives, the best alternative can be gated
方法通過引入基於負理想點下和基於正理想點下的期望值決策矩陣概念，結合決策者的偏好信息，對方案進行排序。 -
This paper applies generalized multipler method to translate convex quadratic programs with equal constraints and non - negative constraints into simple convex quadratic programs with non - negative constraints. the new algorithm is gotten by solving the simple quadratic program. it avoids the computation of inverse matrix and exploits sparsity structure in the matrix of the quadratic form. the results of numerical experiments show the effectiveness of the algorithm on large scale problems
根據廣義乘子法的思想，將具有等式約束和非負約束的凸二次規劃問題轉化為只有非負約束的簡單凸二次規劃，通過解簡單凸二次規劃來得到解等式約束和非負約束的凸二次規劃新演算法，新演算法不用求逆矩陣，這樣可充分保持矩陣的稀疏性，用來解大規模稀疏問題.數值結果表明：在微機486 / 33上就能解較大規模的凸二次規劃 -
4. because there are sub - elements in a member with the introduction of inner joints, when tile spatial stifmess matrix of main joints of a member is made, there are some cases of solving the double nonlinear equations, negative stifmesses, and singular stiffness matrices in process of iterating
4 、由於引入了內結點，構件存在子單元，在形成主節點的構件空間單元剛度矩陣時，存在雙重非線性方程求解，迭代過程中負剛度和剛度矩陣奇異問題。 -
The numerical range of non - negative matrix
非負矩陣的數值域 -
Non - negative matrix factorization and its applications to gene expression data analysis
非負矩陣分解及其在基因表達數據分析中的應用 -
In chapter 4, we research a way how to generate curve by discrete points. the way uses several low - order bezier curve to substitute one high - order bezier curve in order to avoid computing high - order negative matrix. the curve produced by this way has good smoothness
第四章對由離散點構建曲線進行了研究，繞過高階矩陣求逆，把由k個低階的bezier曲線拼合產生的復合曲線來代替單一的高階bezier曲線，並保證曲線之間的光滑過渡。 -
Finally, when the decomposition is proceeding to a symmetric positive definite matrix, the pivot may be very small or even negative. there provided several methods to overcome this shortcoming. ( 2 ) for the block strictly diagonally dominant matrices, there proved the existence and uniqueness of the block lu decomposition and the existence of the incomplete version
（ 2 ）證明了嚴格塊對角占優矩陣塊lu分解的存在唯一性與塊不完全lu分解的存在性，以及嚴格塊對角占優矩陣與不可約塊對角占優矩陣的塊jacobi 、塊gs ，塊sor 、塊ssor等基本迭代法的收斂性。 -
The holistic features are extracted by principal component analysis ( pca ), and the local features are extracted by non - negative matrix factorization with sparseness constraints ( nmfs )
首先通過主元分析演算法（ pca ）提取全局特徵，利用帶稀疏限制的非負矩陣分解演算法（ nmfs ）提取局部特徵。 -
Secondly, we utilize the nmf ( non - negative matrix factorization ) algorithm to extract human face local feature subspace
然後，對獲得的類人臉膚色區域利用nmf （ non - negativematrixfactorization ）非負矩陣分解的方法提取人臉局部特徵子空間。 -
Principle component analysis ( pca ), as a classical method for feature extraction, learns holistic representations of facial images, while non - negative matrix factorization ( nmf ), a recently proposed approach, learns parts - based representations of faces. however, we argue that nmf can not only learn parts - based representations but also holistic ones with different sparseness constraints
在眾多的特徵提取演算法中，基於全局特徵提取的主元成分分析（ principlecomponentanalysis ， pca ）是討論最多的經典演算法，與此對應的是基於局部特徵提取的非負矩陣分解（ non - negativematrixfactorization ， nmf ）演算法。 -
In this thesis, we propose an efficient nmfs + rbf aggregate framework for fr, in which non - negative matrix factorization with sparseness constraints ( nmfs ) is firstly applied to learn either the holistic representations or the parts - based ones by constraining the sparseness of the basis images, and then the rbf classifier is adopted for pattern classification
本文提出了一種基於非負矩陣稀疏分解（ non - negativematrixfactorizationwithsparsenessconstraints ， nmfs ）和rbf神經網路的人臉識別方法。通過控制稀疏度， nmfs演算法既可提取人臉全局也能提取局部特徵，再運用rbf神經網路進行模式分類。 -
As the total negative surface charge of such complexes matches the surrounding charge density of the matrix, the sds - protein complex stops migrating and remains stationary, as typical of steady - state separation techniques
當復合物表面總的負電荷與周圍基質的電荷密度一不能致時，與典型的穩態分離技術相似， sds -蛋白復合物則不再遷移而保持固定。 -
In previous researches, the attentions were mostly paid to the local negative stiffness caused by concrete crack, and in this case the global stiffness matrix was rarely negative
筆者在已有的研究成果基礎上，對由混凝土結構鱉體剛度矩陣變負引起的求解困難提出了相應的解決方案。
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