In this paper we apply the ideas of New Q-Newton's method directly to a system of equations, utilising the specialties of the cost function $f=||F||^2$, where $F=(f_1,\ldots ,f_m)$. The first algorithm proposed here is a modification of Levenberg-Marquardt algorithm, where we prove some new results on global convergence and avoidance of saddle points. The second algorithm proposed here is a modification of New Q-Newton's method Backtracking, where we use the operator $\nabla ^2f(x)+\delta ||F(x)||^{\tau}$ instead of $\nabla ^2f(x)+\delta ||\nabla f(x)||^{\tau}$. This new version is more suitable than New Q-Newton's method Backtracking itself, while currently has better avoidance of saddle points guarantee than Levenberg-Marquardt algorithms. Also, a general scheme for second order methods for solving systems of equations is proposed. We will also discuss a way to avoid that the limit of the constructed sequence is a solution of $H(x)^{\intercal}F(x)=0$ but not of $F(x)=0$.
翻译:在本文中, 我们直接应用 New Q- Newton 方法的想法, 将新 Q- Newton 方法的理念应用到一个方程系统, 使用成本函数的特性 $f $f $F $2$, 其中$F= (f_ 1,\ ldots, f_ m) 。 这里提出的第一种算法是修改Levenberg- Marquardt 算法, 在那里, 我们证明全球趋同和避免马鞍点的一些新结果。 这里提议的第二个算法是修改 New Q- Newton 方法的后跟踪方法, 也就是修改 New Q- Newton 方法的后跟踪方法 。 另外, 我们使用操作者$ @ 2f (x) delta $ * = $2f (x) $2\\\\\\\\\\\\\ tau} $。 我们还将讨论如何避免新 New New New New New New Newton 方法的 方法本身, 而目前比 Leven levelgenger- Marqards (x) 解 。