So, then we've seen the method of Lagrange multipliers.
我们就此学过拉格朗日乘数法的。
And so what we will see is you may have heard of Lagrange multipliers.
接下来要讲到的，就是你们可能听说过的拉格朗日乘数法。
Chapter 13 contains an excellent exposition of the Lagrange multipliers technique.
这本书的第13章对拉格兰兹乘数法有非常精辟的讲解。
The unknown function F can be easily identified like the identification of Lagrange multipliers.
而待定函数F的识别类似于拉氏乘子的识别。
The FEM calculate method for contact problem, i. e. LAGRANGE multipliers, penalty methods and direct constrains were discussed.
同时探讨了接触问题的三种计算方法——拉格朗日乘子法、罚函数法和基于求解器的直接约束法；
One of them is to find the minimum of a maximum of a function when the variables are not independent, and that is the method of Lagrange multipliers.
其中一个是找出一个函数的极小值，极大值，这个函数的变量是相关的，这种方法称为拉格朗日乘数法。
Expect one about a min/max problem, something about Lagrange multipliers, something about the chain rule and something about constrained partial derivatives.
有一个极值问题，也有关于拉格朗日乘数法的，链式法则也会有的,约束条件下偏导数当然不会漏掉。
This paper treated discontinuous medium boundary condition by using visual principle and through a more convenient method of Lagrange multipliers method.
本文利用可视原则对不连续介质边界条件等效处理，通过一种更简便的拉格朗日法施加不连续边界以及本质边界条件。
OK, so last time we saw how to use Lagrange multipliers to find the minimum or maximum of a function of several variables when the variables are not independent.
上次我们看了，怎样利用拉格朗日算子，去求解一个受约束的，多变量函数的最大最小值。
Moreover, a weight optimization scheme for the multi-kernel was proposed by maximizing the Margin Maximization Criterion(MMC)based on the method of Lagrange multipliers.
进而，使用拉格朗日乘子法优化最大边缘准则（MMC），提出了多重核权值优化算法。
Furthermore, utilizing the Lagrange method of multipliers and the implicit theorem to work out the critical value which makes one of those inequality locally inverted.
然后利用拉格朗日乘数法与隐函数定理，求出了使其中一不等式局部反向的临界值。
Furthermore, utilizing the Lagrange method of multipliers and the implicit theorem to work out the critical value which makes one of those inequality locally inverted.
然后利用拉格朗日乘数法与隐函数定理，求出了使其中一不等式局部反向的临界值。
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