系数矩阵

The main results of this research are as follows:(1) A parallel algorithm for solving dense matrix linear equations on distributed-memory multi-computer is presented. Convergent velocity of this algorithm is better than parallel Jacobi method"s, and parallelism is better than Gauss-Seidel method"s. According to theoretical analysis, convergent conditions are given. Moreover numerical experiments indicate that results agree with theory.

主要完成了如下研究工作：(1)提出了一种求解系数矩阵为稠密矩阵的线性方程组的适合于MIMD分布式存储的并行迭代算法，该算法设计上兼取了Jacobi算法并行性好的优点和Gauss-Seidel算法收敛速度快的长处，并且在理论上给出了该算法成立的收敛性条件，并通过数值计算验证了此算法结果与理论相符合。

In the iterative, the constant matrixB'and B take the place of variable Jacobian matrix.

这种算法在迭代过程中以不变的系数矩阵和代替变化的雅克比矩阵B'和B''，可以节省存储空间、提高计算速度。

In terms of order of industrial development, this thesis uses industrial engineering theory, establishes relevant coefficient matrix of leading industry choosing criterion and correlative effect matrix, calculates leading industry of Hebei province.

在工业行业发展序列的选择上，运用工业工程理论，建立主导产业选择基准相关系数矩阵和关联效应矩阵，测算比选出河北省工业主导产业。

This paper investigates alternating iterative method and generalized alternating method for the solution of a large linear system, extend the convergence theorem and comparison theorem for generalized or alternating iterative method when the coefficient are Hermitian positive definite systems.

本文主要研究了大型线性方程组的交替迭代法及迭代法的各种变形，给出了当系数矩阵为Hermitian正定矩阵时各类迭代法的收敛原理及其相应的比较理论。

Based on ear recognition, an improved NMFSC(Nonnegative Matrix Factorization with Sparseness Constraints) method was proposed by imposing an additional constraint on the objective function of NMFSC, which could capture the semantic relations of coefficient matrix as orthogonal as possible. The interated rules to solve the objective function with the constraint were presented, and its convergence was proved.

针对人耳识别问题，提出了一种改进的稀疏性受限的非负矩阵因子方法，通过增加一个使系数矩阵尽可能正交的约束条件来定义原目标函数，给出求解该目标函数的迭代规则，并证明迭代规则的收敛性。

Based on ear recognition, an improved NMFSC (Non-negative Matrix Factorization with Sparseness Constraints) method was proposed by imposing an additional constraint on the objective function of NMFSC, which could capture the semantic relations of coefficient matrix as orthogonal as possible. The interated rules to solve the objective function with the constraint were presented, and its convergence was proved.

针对人耳识别问题，提出了一种改进的稀疏性受限的非负矩阵因子方法，通过增加一个使系数矩阵尽可能正交的约束条件来定义原目标函数，给出求解该目标函数的迭代规则，并证明迭代规则的收敛性。

This paper analyses the LR factorization of matrix,and improves the algorithm based on recursive algorithm and iteration,and brings forth the developed method of matrix factorization,which accelerates the convergence speed of the factorization.

将方程组系数矩阵的LR分解算法过程加以改进，加入递归算法，使矩阵产生分块。

The way of solving matrix equation directly with primary transformation method is discussed with the premise of the matrix of coefficients being reversible, which makes the solving procedures more simple.

讨论了在系数矩阵可逆的前提下，如何用初等变换的方法直接求解矩阵方程，使求解过程更简化，同时给出一般线性方程组的初等变换直观解

For the first-order ordinary differential equation system, the coefficient matrix of variables with derivative is decomposed into the triangular factor form and transformed into unit matrix.

对于一阶常微分方程组，将具有导数变量的系数矩阵作三角化分解，使其简化成单位矩阵。

Firstly, we apply block AOR method to find the least square solution of minimal norm to the rank deficient linear systems where A is a complex m*n matrix with rank k.

首先，我们把求解线性方程组的块加速超松弛迭代法应用于求解亏秩线性方程组的最小范数最小二乘解，其中线性方程组的系数矩阵A是秩为k的m*n复矩阵。

But we don't care about Battlegrounds.

但我们并不在乎沙场中的显露。

Ah! don't mention it, the butcher's shop is a horror.

啊！不用提了。提到肉，真是糟透了。