梯度法

METHODS: Rat BMSCs were isolated by density gradient method and cultured in 3 different concentrations of oxygen.

采用密度梯度法分离培养大鼠骨髓间充质干细胞，在3种氧浓度中进行培养。

It was introduced that extraction technics of soybean protein concentrate by continuous gradient method.

介绍了连续梯度法萃取大豆浓缩蛋白的生产工艺。

One points at a sequence of one sparse linear algebra system of equation ,utilizing frequent treatment sparse matrix data structure at present that is according to the competent store structure, design the law of conjugation gradient method which solves the equation group of the sparse linear algebra of asking analyses the complexity of calculating.

第一部分针对一类稀疏线性代数方程组，利用目前国际上使用比较频繁的处理稀疏矩阵的按行稀疏存储结构，设计了求解稀疏线性代数方程组的共轭梯度法，并分析计算复杂度。

The one order differential model and convolutional model of impedance formula of amplitude versus offset inversion were established. Impedance inversion formula from AVO was derived based on Bayesian framework. Methods of using Huber function as prior model parameter distribution and covariance matrix from well log as constrains were developed. The P-wave impedance, S-wave impedance and density were calculated by the conjugate gradient algorithm.

为此建立了振幅随偏移距变化波阻抗反演公式的一阶差分模型及褶积模型，推导了基于贝叶斯理论的AVO波阻抗反演公式，给出了采用Huber分布作为模型参数的先验分布及测井数据的参数协方差矩阵作为约束条件的实现方法，并利用共轭梯度法计算了纵、横波阻抗及密度。

It is difficult to solve the optimal iteration step and Lagrange multiplier in the gradient optimal power flow solutions. The saddle node iteration method was applied to solve the above problems based on a certain supposition.

在梯度法最优潮流的求解过程中，确定不等式约束的拉格朗日乘子以及求取最优步长等比较困难，文中在采取一定假设的基础上，运用鞍点迭代算法进行上述问题的求解。

Preconditioned con- jugate gradient algorithm is a fast and accurate computational algorithm.

预条件共轭梯度法是一种精确并且收敛迅速的计算方法。

The PetrovGalerkin formulation is applied to solve the genera lized Stokes problem in each subdomain, and the Lagrange multiplier problem on the interfaces is solved using an algorithm of conjugated gradient. Velocity, density and Lagrange multiplier are approached in the spaces of continue piecewise linear functions.

应用PetrovGalerkin方法解每个子域上的广义Stokes问题，而交界面上的Lagrange乘子则通过共轭梯度法迭代求解，各变量均由线性函数离散。

Its global convergence and linear convergence rate were proved under some mild conditions.

提出一类新的求解无约束优化问题的记忆梯度法，在较弱条件下证明了算法具有全局收敛性和线性收敛速率。

On the base of the good convergence of FR, and in view of the descend property of the paper presents a new conjugate gradient method, and studies the global convergence with two kinds of Armijo-type linear search.

基于FR方法好的收敛性并考虑到d的下降性，提出了一类新的共轭梯度法，并在两种Armijo型搜索下，研究了新方法的全局收敛性。

Numerical examples show that the least- squares images can be efficiently retrieved in a few iterations of conjugate gradients method.

数值实例表明，通过少数的共轭梯度法迭代，就能得到与真实模型差别很微小的偏移效果。

Plunder melds and run with this jewel!

掠夺melds和运行与此宝石！

My dream is to be a crazy growing tree and extend at the edge between the city and the forest.

此刻，也许正是在通往天国的路上，我体验着这白色的晕旋。