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The classic iterative ones need special characters of the coefficient matrix; CG has over linear convergence, but the coefficient matrix is positive definite; Krylov subspace ones can deal with non-symmetric linear systems, but sometimes it must face"collapse"problems.

经典迭代法的收敛需要由系数矩阵的一些特定性质来保证;共轭梯度法具有超线性收敛性,但是系数矩阵必须是正定矩阵;Krvlov子空间法可用于非对称矩阵问题,但可能出现崩溃现象。

Lyapunov second method is applied to analysis of partial stability of equilibrium of linear ordinary differential equation with constant coefficients, the problems on partial stable matrix, partial positive definite matrix and Lyapunov matrix equation are studied.

将Lyapunov第二方法用于研究常系数线性系统零解的部分变元渐近稳定性,可引出相关的一些特殊矩阵问题,包括部分稳定矩阵、部分位正定矩阵、矩阵方程的可解性等。

This condition only requires finding a common positive definite matrix in each maximal overlapped-rule group.

在此基础上,提出了一个新的判定系统稳定性的充分条件,该条件仅需在每个最大交叠规则组中分别寻找各自公共的正定矩阵。

This condition only requires finding a common positive-definite matrix in each maximal overlapped-rule group. It can reduce the difficulty of former stability analysis approaches.

该条件只需在各最大交叠规则组内分别寻找公共的正定矩阵,减小了以往稳定性判定方法的局限性和难度。

In this paper,new quadratic PEk method and quadratic EPEk method are given for solving a system of linear algebraic equations whose matrix of coefficients is tridiagonal blocked matrix.

建立求解系数矩阵为分块三对角矩阵的线性代数方程组的新型二次PEk方法以及其外插迭代二次EPEk方法,对系数矩阵为对称正定矩阵情形,证明了新型二次PEk方法和二次EPEk方法的可解性和收敛性

The calculus of maxima and ''.

正定积分的极大与极小的微积分学。

Some sufficient and necessary conditions of the full symmetric real matrix is full definite matrix are discussed.

讨论了全对称实矩阵是全正定矩阵的几个充分必要条件。

Then A is positive semidefinite, negative definite and negative semidefinite.

则A是半正定,负定,半负定的。

Positive semi-definite matrices are positive definite if and only if they are nonsingular.

正半定矩阵是正定的,当且仅当它们是非奇异矩阵。

Missirlis in article [1]. At the same time, a sufficient condition for convergence of the PSD method is given to be compared when the coefficient matrix A of the linear system Ax = b is a symmetric, positively defective matrix. In §3.2, an example is given to state that the range of our sufficient condition is wider than theorem 3.3 of article [1]. On the other hand, following a.n analogous approach of [14] and starting the functional relationshipwe have a perfect analysis for the PSD method to converge and optimum valves for the involved parameters under different conditions.Under the assumptions that A is a consistent ordered matrix with nonvanishing diagonal elements and the eigenvalues of the Jacobi matrix of A are real,we get necessary and sufficient conditions for the PSD method to convergence.The result is equal to theorem 1 of article [9].Under the same condition, we can see the optimal parameter and of corresponding spectral radius of thePSD method in [8]:(2)When A is a consistent ordered matrix with nonvanishing diagonal elements and the eigenvalues of the Jacobi matrix of A are imaginary or zero,we get necessary and sufficient conditions for the PSD method to convergence.In chapter 3, the optimal parameter and of corresponding spectral radius of the PSD method are given by table 3.3. Moreover, under the assumption 0

Missirlis在文献[1]中定理3.3的不准确,同时给出了当线性方程组Ax=b的系数矩阵A为对称正定阵时,PSD迭代法收敛的一个充分条件与之比较,并且在§2.3中用实例说明了对于一部分矩阵而言本文得到的充分条件广于[1]中定理3.3的充分条件;另一方面,按照文献[14]的方法,我们从PSD迭代法的特征值λ与其Jacobi迭代矩阵B的特征值μ的关系式:出发,在不同条件下对PSD迭代法的收敛性和最优参数以及最优谱半径进行了完整的分析:(1)在系数矩阵A为(1,1)相容次序矩阵且对角元全不为零,其Jacobi迭代矩阵B的特征值全为实数的条件下,给出了PSD迭代法收敛的充分必要条件,此结果与[9]中的定理1等价,此时最优参数及最优谱半径由[8]得:(2)第三章表3.3中给出了,当系数矩阵A为(1,1)相容次序矩阵且对角元全不为零,其Jacobi迭代矩阵B的特征值全为纯虚数或零时的PSD迭代法的收敛范围和最优参数,并且我们可以得到当0

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在后面是与变速箱,离合器,差的创新结合变速,和内侧安装鼓式制动器。

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我希望你可以获得幸福。。。