递归的高阶迭代映射家族
Recursive families of higher order iterative maps
AI总结：
本文提出高阶收敛迭代映射家族，基于内积模型函数，递归定义的牛顿-巴耶中心映射用于解决最小子集问题和Ackley函数的多极值定位。
摘要：
为了近似方程的简单根，我们构造了高阶收敛的迭代映射家族。这些映射基于可写成内积形式的模型函数。主要讨论的映射家族递归定义，称为牛顿-巴耶中心映射。我们通过两个实例展示了牛顿-巴耶中心映射的应用，一个处理典型的最小二乘问题，另一个展示如何同时定位Ackley函数的大量极值。
英文摘要：
To approximate a simple root of an equation we construct families of iterative maps of higher order of convergence. These maps are based on model functions which can be written as an inner product. The main family of maps discussed is defined recursively and is called {\it Newton-barycentric}. We illustrate the application of Newton-barycentric maps in two worked examples, one dealing with a typical least squares problem and the other showing how to locate simultaneously a great number of extrema of the Ackley's function.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
