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解线性方程组的雅克比法，可指定精度和迭代次数-Conjugate gradient method for linear equations
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共轭梯度法，用于机械优化设计中的无约束优化方法的求法，基于二元函数。-Conjugate gradient method, the optimum design of the machine used for unconstrained optimization method the method, based on binary function.
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用共轭梯度法解线性方程组解决解析方法解不了的方程。-Conjugate gradient method for solving linear equations to solve the analytical method solution of the equation can not
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共轭梯度法和高斯赛德尔迭代法的经典matlab程序-Conjugate gradient method and the high Sisaideer iterative method classic matlab program
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工程优化中用FR共轭梯度法求最值，采用的是教科书上的经典算法步骤，简单易懂，可以进行参考。-The most value engineering optimization using FR conjugate gradient method, using the classic steps of the algorithm in the textbook, easy to understand, you can reference.
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本程序用共轭梯度法求函数局部极小值。程序包括三个文件，主程序conjugategradient，函数的梯度gradient，以及黄金分割法partition精确求一维搜索极小点变量步长。程序用来求多变量函数的极小值。-This program conjugate gradient method and function of local minima. The program includes three files, the main conjugategradient function gr
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ICCG_BJ法，预测共轭梯度法求解大型线性方程组
A[M][N]*x[N]=b[M]-ICCG_BJ France, BJ forecast conjugate gradient method for solving large linear equations
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ICCG_SSOR法
用于预测共轭梯度法求解大型线性方程组A[M][N]*x[N]=b[M]-ICCG_SSOR method for predicting the conjugate gradient method for solving large linear equations A [M] [N]* x [N] = b [M]
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共轭梯度法的资料，共轭梯度法为解解线性方程组的一类迭代法可直接使用。
-Conjugate gradient method, data, and the conjugate gradient method for the solution to solving linear equations, an iterative method can be used directly.
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比较了三种学习方法 1 gradient descent 2 steepest descent with line search
3 conjugate gradient method. 三种方法都在一个.m文件中被实现。-compare three learning methods: 1 gradient descent 2 steepest descent with line search
3 conjugate gradient method.
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优化设计方法：共轭梯度法的c语言言程序。初学入门者适用
-Optimal design method: conjugate gradient method c language statement was made by the program. Beginners Getting Started applicable
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Sample code for optimization based on Gradient base. include BFGS, Steepest Descent method, DFP method, Conjugate Gradient method ans so on-Sample code for optimization based on Gradient base. include BFGS, Steepest Descent method, DFP method, Conjug
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利用共轭梯度法（CG+）求解大规模无约束最优化问题，代代码所用语言为Fortran77.，
-The conjugate gradient method (CG+) for solving large-scale unconstrained optimization problems, the generation of code language is Fortran 77.
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可实现的算法：软件说明：
1.全主元高斯约当消去法2.LU分解法3.追赶法4.五对角线性方程组解法5.线性方程组解的迭代改善6.范德蒙方程组解法7.托伯利兹方程组解法8.奇异值分解9.线性方程组的共轭梯度法10.对称方程组的乔列斯基分解法11.矩阵的QR分解12.松弛迭代法第2章插值1.拉格朗日插值2.有理函数插值3.三次样条插值4.有序表的检索法5.插值多项式6.二元拉格朗日插值-The algorithm can be realized: Software Descr iption:
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共轭梯度法可以实现正定线性方程组的求解，并可以通过实例进行验证-Conjugate gradient method can achieve positive definite linear equations, and can be verified by an example
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共轭梯度法计算线性方程组的代码。本段代码采用了F90的风格书写。注意共轭梯度法只适用于对称正定的矩阵。-Conjugate gradient method to calculate the linear equations of the code. The section of code uses the the F90 style of writing. Note conjugate gradient method is only applicable to symmetric positiv
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无约束多维极值问题，包含
用模式搜索法求解多维函数的极值
用Rosenbrock法求解多维函数的极值
用单纯形搜索法求解多维函数的极值
用Powell法求解多维函数的极值
用最速下降法求解多维函数的极值
用共轭梯度法求解多维函数的极
用牛顿法求解多维函数的极值
用修正牛顿法求解多维函数的极值
用DFP法求解多维函数的极值
用BFGS法求解多维函数的极值
用信赖域法求解多维函数的极值
用显式最速下降法求正定二次函数的极值
-Unconstrain
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大型对称方程组解算（Fortran90）：
共轭梯度法、高斯消元法和平方根法-Large symmetric linear solver (Fortran90): conjugate gradient method, Gaussian elimination and the square root method
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包含线性方程组迭代解法的共轭梯度法和最速下降法Matlab源代码级收敛性分析报告，以及线性方程组Matlab解法的参考资料-Contains linear equations iterative method for solving the conjugate gradient method and the steepest descent method Matlab source-level convergence analysis report, as well as linear equa
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多元函数的共轭梯度法，配有实际调用的例子与输入数据-Multivariate function conjugate gradient method, with the example of the input data of the actual call
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