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无约束最优化当中经典的拟牛顿法matlab程序-Unconstrained optimization among classical quasi-Newton method matlab program
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Neural Predictive Control using Quasi Newton Optimization
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BFGS拟牛顿法求非线性无约束最优化(函数极值)问题-BFGS quasi-Newton method for solving nonlinear unconstrained optimization (function extremum) problem
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DFP拟牛顿法求解非线性无约束最优化问题(函数极值)-DFP quasi-Newton method for solving nonlinear constrained optimization problem (function extremum)
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最优化算法中的拟牛顿法,是一种非线性算法问题-Optimization algorithm quasi-Newton method, is a nonlinear algorithm problems
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解决了最小无约束优化问题 步长由ARmijo非精确一维搜索生成,迭代方向分别由最速下降法,阻尼牛顿法,共轭梯度法,拟牛顿法(BFGS)产生(This code solves the minimum unconstrained optimization problem, and the step size is generated by ARmijo inexact one-dimensional search. The iterative directions are generated b
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牛顿迭代法是解非线性方程组比较经典的方法;
拟牛顿法是为了解决求Jacobi矩阵时带来的困难,现已成为解决非线性方程组和最优化问题的最有效方法之一。(The Newton iterative method is a classic method for solving nonlinear equations.
The quasi Newton method is one of the most effective methods for solving the nonlinear equat
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基于拟牛顿法解决无约束优化问题的Python代码(Python code for unconstrained optimization based on quasi-Newton method)
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