The algorithm summarizes Newton’s Method.
软件应用简介

Newton’s method uses information from the Hessian and the Gradient i.e. convexity and slope to compute optimum points. For most quadratic functions it returns the optimum value in just a single search or 2 iterations which is even faster than Conjugate Gradient method. This can be verified by comparing the results with Conjugate Gradient algorithm previously posted by me. However, in some cases for higher order or non-quadratic functions the method might diverge or it may converge to non-minimum stationary points. To guarantee convergence at minima often pre-conditioners are used. The pre-conditioners limit step size increasing the number of computations, but ensuring minimum solution.
界面展示

结果示意

规格 价
0元试用 |
---|
0.0元人民币/月 |
声明:本站部分文章及图片源自用户投稿,如本站任何资料有侵权请您尽早请联系jinwei@zod.com.cn进行处理,非常感谢!