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modular matrix相关的网络例句

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The paper simplifies the joint diagonalization of matrices into optimization problem which only includes the eigen matrix. For solving the problem conveniently, each row vector of the eigen matrix is parameterized, then utilizes the improved genetic algorithm to get the optimal parameter.

摘要该文首先将矩阵联合对角化问题化简成一个只含有特征矩阵的优化问题,为了便于求解,文中将待求特征矩阵的每一列向量进行参数化处理,并利用改进的遗传算法寻找最优的新参数。

Divide the whole region D into finite units and corresponding link points may be obtained. Constructing the equation of variation calculation about every element leads to the finite number of equations. Further more, algebra equation group for general synthesis are gained by adding these finite number of equations, that is,{T}={P} where is the coefficient matrix of the equation group, or say the temperature rigidity matrix,{T} is the row vector of unknown temperature and {P} is the row vector of the terms on the right side of the equation.

然后将整体区域D划分成有限个单元并得到相应的有限个节点,从而可以得到关于每个单元的变分计算方程,将这有限个方程相加就得到了总体合成的代数方程组,即{T}={P},其中为方程组的系数矩阵,也称温度刚度矩阵,{T}为未知温度值的列向量,{P}为等式右端项组成的列向量。

In the case of small number of samples, the between-class scatter matrix S〓 is a singular matrix.

作者企图在目前的基础上继续在这方面作出努力。

This is a matrix that causes no effect when it's concatenated with another matrix of the same dimensions.

单位矩阵在和另一个相同维数的矩阵连接时没有任何效果。

Matrix's triangular decomposition is the simplest and most basic kind of decomposition in matrix decomposition .

矩阵的三角分解是矩阵分解中最简单、最基础的一种。

The assignment matrix model proposed in this thesis is more applicable for freeway's dynamic OD matrix estimation.

Ashok的随机分配矩阵模型,以期在本文中尽可能包含目前计算分配矩阵较新的方法。

The algorithm reduces the dimension of the input vectors by using the Toeplitz technique for the sample correlation matrix and needs only the first column of the processed matrix.

该算法仅将Toeplitz化后的采样协方差矩阵的第一列元素作为网络输入,从而降低了输入矢量的维数。

The algorithm processes very few snapshot data opposed to forming sample covariance matrix and computing matrix inversion.

它无需构造协方差矩阵及进行矩阵求逆,又避免了复杂度较高的广义特征值分解。

For the case where the sample covariance matrix is unknown or the sample support is not sufficient to form the sample covariance matrix, we carry out the spatially smoothed CSA-MSWF to quickly find the signal subspace and the noise subspace.

如果阵列协方差矩阵是未知的,我们采用空间平滑的CSA-MSWF快速计算信号子空间和噪声子空间的基矢量。

The asymptotical properties of KdV equation and KP equation exhibit the soliton behavior when some conditions are satisfied, and in some cases the parameter matrices describing the interaction between two solutions is quite simple. Two kinds of solutions of the second coupled equations of AKNS hierarchy are provided and applied to NLS equation. A systemical way of construction of special solutions is also tried for DS equation. Most of the results on a scalar equation can often be directly generalized to some matrix equation, and the difference between the ω in scalar form and ω in matrix form lies only in the replacement of vector p, q by matrices p, q.

对KdV方程和KP方程渐近性质的讨论显现出解在一定条件下的孤子特性,从而使得一些情形下,同类解的相互作用体现在参数矩阵上变的较简单;我们给出了AKNS方程的两类不同解,并约化到NLS;对DS方程,我们从另一个方面初步探讨了形式化推导矩阵方程特解的方法;把这些有关标量ω的结果推广到ω为矩阵上往往只要把p,q变为矩阵即可,进而可以再推广到方程组上。

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You can snipe the second and third union leaders from this position.

您可以鹬第二和第三工会领袖从这一立场出发。

Aiming at the currently shortage of XML streams quality detecting, this paper proposes a new forecasting method of XML streams quality by least squares support vector machines, which is used the method of XML keys' vector matrix as windows, and vector product wavelet transform to multilevel decompose and refactor the XML streams series, that can fulfill real-time checking demand of XML quality, and ensure constraint, consist- ency and integrality. For even more adapting net load, it proposes a control strategy by weight and adaptive adjustment to ensure XML streams quality.

针对当前XML数据流质量检测存在的不足,提出构建XML键的矢量矩阵作为窗口,利用矢量积小波变换多级分解与重构XML数据流,再结合最小二乘支持向量机对XML数据流质量进行预测的一种方法,满足XML数据流质量重构时实时检测的要求,保证XML数据的约束性、一致性与完整性;为了更好的适应网络负载,采取加权与自适应窗口调整等调度策略充分保证XML数据流的质量检测。

This is a very big challenge to developers especially that Ajax is constantly changing.

这对开发者来说是一个非常大的挑战,尤其是需要不断变化的Ajax。