Sensitivity analysis of the change of basis vector;
基向量变化的灵敏度分析
A discussion of basis vector is prepared.
本文中采用移动最小二乘法(MLSM)构造形函数,并利用罚函数法引入本质边界条件,通过算例讨论了无网格法中基向量的选取问题。
A new basis vector is defined for the Krylov subspace,which is preconditioned by a preconditioning factor.
利用正交级数对材料和外荷载随机场进行离散;利用刚度矩阵在随机场均值处的逆矩阵作为预处理因子,定义一组随机子空间的新的基向量,将结构随机响应过程展开为该组随机基向量的线性表达式,首次提出了预处理谱随机变分原理,在此基础上建立了结构随机分析的预处理谱随机有限元法。
The basis vectors of the natural images were obtained by using fast conjugate gradient algorithm.
文中利用双梯度算法对自然图像的基向量进行迭代学习。
Primer vector method is a geometric method for obtaining optimal solutions of the rendezvous between elliptical orbits of low eccentricity.
基向量法是求解近圆轨道间固定时间最优交会的一种几何方法。
Aimed at the problem of obtaining the primer vector curves for the optimal solutions,a new method based onfuzzy inference is proposed.
基向量法是求解近圆轨道间固定时间最优交会的一种几何方法,本文针对基向量法中最优解的基向量曲线的求解问题,提出一种基于模糊推理的求解方法,使得基向量法的整个求解过程可以脱离人工干预完全由计算机完成,从而使基向量法求解的效率有了本质上的提高。
This paper proposes a new method to construct wavelets decomposing and reconstructing matrices of wavelet coefficients without iterative calculation in symmetrical extension for finite length signal,and correspondingly gives the base vectors and basis images of 9/7 wavelet.
给出了对称延拓方式下有限长信号不需逐级计算而直接得到小波系数的分解矩阵和由这些小波系数重构原信号的重构矩阵的构造方法,并给出了常用的相应于9/7小波的分解矩阵和重构矩阵及其基向量,它们可广泛用于基于小波的图像分块处理中。
The idea of this algorithm bases on Rm=(A)(A)⊥,filling(A)⊥matrix with base vectors of A,which makes A matrix transform into nonsingular matrix A.
算法的思想基于Rm=(A)(A)⊥,用(A)⊥的基向量补充到矩阵A中,使A变成非奇异方阵A~。
By mapping image character points to radial basis vector(RBV)space, the transition matrix and similarity between two character point sets are constructed by SNN kernel function.
将图像中的特征点映射到径向基向量(Radial basis vector,RBV)空间,利用SNN核函数计算两个特征点集的相似度及过渡矩阵。