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With PRP conjugate gradient method for solving unconstrained problem
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wolf Searches PRP conjugate gradient method
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共轭梯度法(Conjugate Gradient)是介于最速下降法与牛顿法之间的一个方法,它仅需利用一阶导数信息,但克服了最速下降法收敛慢的缺点,又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点,共轭梯度法不仅是解决大型线性方程组最有用的方法之一,也是解大型非线性最优化最有效的算法之一。这里给出共轭梯度法的源程序-Conjugate gradient method (Conjugate Gradient) is between the steepest descent method and
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共轭梯度法(Conjugate Gradient)是介于最速下降法与牛顿法之间的一个方法,它仅需利用一阶导数信息,但克服了最速下降法收敛慢的缺点,又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点,共轭梯度法不仅是解决大型线性方程组最有用的方法之一,也是解大型非线性最优化最有效的算法之一-Conjugate gradient method (Conjugate Gradient) is between the steepest descent method and Newton' s
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共轭梯度法,用于求解非线性约束问题,适用于matlab程序-Conjugate gradient method for solving nonlinear constrained problem for matlab program
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共轭梯度法解决矩阵方程问题-Conjugate gradient method to solve the matrix equation problem
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用共轭斜量法求解n阶方程组,记录达到所需精确解的迭代次数。-Conjugate Gradient Method with solving n-order equations, exact solutions of the desired record number of iterations.
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本程序是运用共轭梯度法的数值计算方法来求解正定对称矩阵方程。-This procedure is to use the conjugate gradient method numerical method to solve symmetric positive definite matrix equation.
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数学计算中CG法应用举例,CG法又名共轭梯度法,是一种常用的数学计算方法。-Application of mathematical calculations CG example, CG method known as conjugate gradient method, is a commonly used mathematical calculations.
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使用FR共轭梯度法求解无约束问题
输入包括初始点,目标函数和梯度
输出包括最优点和最优解,还有迭代次数-Use FR conjugate gradient method for solving unconstrained problems including initial entry points, the objective function and the gradient of the output, including the advantages and the most o
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病态方程组的数值解法,Guass,Jacobi,SOR iteration,conjugate gradient method-numerical solution of ill-conditioned system of equations,Guass,Jacobi,SOR iteration,conjugate gradient method
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改进的共轭梯度法,具有很好的收敛效果,达到整体最有,在MATLAB中实现。-Improved conjugate gradient method, has a good convergence effect, to achieve the overall most realized in MATLAB.
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本matlab程序用共轭梯度法来求解多元模型的最小值(给出最小值和精度情况)-The matlab program conjugate gradient method to solve the minimum multivariate model (given the minimum and the accuracy of the situation)
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Conjugate Gradient Method
by Yi Cao
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利用Jacobi迭代法和共轭梯度法来解线性方程组的matlab源代码-Use Jacobi iteration method and conjugate gradient method for solving linear equations matlab source code
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共轭梯度法(Conjugate Gradient)是介于最速下降法与牛顿法之间的一个方法,它仅需利用一阶导数信息,但克服了最速下降法收敛慢的缺点,又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点,共轭梯度法不仅是解决大型线性方程组最有用的方法之一,也是解大型非线性最优化最有效的算法之一。-Conjugate Gradient Method (Conjugate Gradient) is between the steepest descent method between a law an
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多变量寻优的源码,包括基本算法如下:DFP法(又称变尺度法),BFS法、一阶梯度法,共扼梯度法。-Multivariate optimization of the source code, including basic algorithm is as follows: DFP method (also known as variable metric method), BFS method, a ladder degree method, conjugate gradient method.
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解线性方程组的迭代法:(1)雅克比迭代法(2)高斯-赛德尔迭代法
(3)松弛迭代法(4)共轭梯度法-Iterative Techniques in Matrix Algebra:(1)The Jacobi Iterative Techniques (2)Gauss-Siedel Iterative Techniques
(3)sor method
(4)The Conjugate Gradient Method
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一种基于共轭梯度法的粒子群算法,对全局最优值进行梯度搜索-Conjugate gradient method based on particle swarm algorithm for the global optimum gradient search
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共轭梯度FR法求解非线性优化最小值问题 -FR conjugate gradient method for solving nonlinear optimization problem minimum
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