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共轭梯度法CGmatlab程序 解线性方程组-Conjugate gradient method matlab program for solving linear equations
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最优化方法中共轭梯度法的matlab程序-Optimization method of conjugated gradient method matlab program
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VC实现的,多维函数搜索,无约束优化方法,
(1)最速下降法 (2)阻尼牛顿法(3)共轭梯度法 (4)鲍维尔法(5)变尺度法(6)单纯形法
-VC implementation, multi-dimensional function of search, unconstrained optimization methods, (1), steepest descent method (2) damped Newton' s method (3) conjugate gradient
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压缩包里包含了无约束优化问题常用的几种求解方法的源程序:变量轮换法(variable_rotation.m)、最速下降法(steepest_descent.m)、修正牛顿法(modified_newton.m)、共轭梯度法(conjugate_gradient.m)。另外,coefficient_matrix.m为目标函数系数获得矩阵,minval.m为最小值计算函数,gradient.m为梯度计算函数-Compression bag contains unconstrained optimiz
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共轭梯度法,是数值分析中很重要的一种,源码为其在matlab中的实现。-Conjugate gradient method, numerical analysis is a very important one in the matlab source code for its realization.
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共轭梯度法源程序,可以再vc++下进行运行-Conjugate Gradient Method source
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matlab程序,1文件功能用FR共轭梯度法求解无约束问题,2、3文件分别表示目标函数和梯度-matlab program, a file function with FR conjugate gradient method for solving unconstrained problems, 2,3 document represent the objective function and gradient
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用FR共轭梯度法求解无约束问题: min f(x)-By FR conjugate gradient method for solving unconstrained problem: min f (x)
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Conjugate Gradient method implemented by matlab
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机械优化设计中的共轭梯度算法 优化二维方程-Conjugate Gradient
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应用共轭梯度法解微分方程的MATLAB代码-A matlab code of conjugate gradient method used for solving the differential equation.
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功能:用FR共轭梯度法求解无约束问题:min f(x)
输入:x0是初始点,fun,gfun分别是目标函数和梯度
输出:x,val分别是近似最优点和最优值,k是迭代次数-Features: use FR conjugate gradient method to solve the unconstrained problem: min f (x)
input: x0 is the initial point, fun, gfun is the objective functio
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conjugate gradient algorithm for echo cancellation. adaptive filter for noise canellation
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the conjugate gradient method,-This article presents a three-containing conjugate gradient method, and prove the algorithm decline and global convergence, which demonstrate the effectiveness of the algorithm.
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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。 在各种优化算法中,共轭梯度法是非常重要的一种。其优点是所需存储量小,具有步收敛性,稳定性高,而且不需要任何外来参数。-Conjugate gradient method (Conjugate Gradie
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数值计算方法中利用共轭梯度法求解正定对称矩阵方程-Conjugate gradient method for solving symmetric positive definite matrix equation
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Preconditioned conjugate gradient method for 2D poisson equation
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Conditional Gradient Method algorithm
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Conjugate Gradient Method
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Conjugate Gradient Method for finding minimum of funcitons
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