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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) between the steepest descent between law and Newton'
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基于matlab软件的一个无约束优化问题的最速下降算法-Based on matlab software an unconstrained optimization problems steepest descent algorithm
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本代码为《最优化理论与方法》书籍中的拥有Amijo改进的最速下降法算法的代码,并举了3个书上的作业题的例子,本代码中的目标函数和约束等初值可由需要进行改变,来得到所期望的计算-The code for the " optimization theory and method" books have Amijo improvement in the steepest descent method algorithm code, citing the three books on
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PSO算法和最速下降法混合算法,求解单目标优化问题,测试函数是非线性方程组,解决MinF(x)的问题。-PSO algorithm and steepest descent method hybrid algorithm for solving single-objective optimization problem, the test function is non-linear equations, solving MinF (x) of the problem.
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最优化问题中的最速下降法,共轭梯度法,黄金分割法代码,为applied optimization with matlab programming书中源代码-Steepest descent method, conjugate gradient method, golden section method code
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