论文总字数：19143字

摘 要

摘要：插值法是通过二维平面几个已知点构造多项式函数。作为n次多项式，通过构造重心型插值基函数，重心型插值函数的问题。的本质思路是将其他的公式来写，通过重心型插值条件确定待定函数，然后计算。对估计串联结构机器学习基于重心型插值拉格朗日重处理，借助于尺度转换将估计串联结构机器学习基于重心型插值拉格朗日重心型插值法分析的，同时利用差值串联结构机器学习基于重心型插值拉格朗日重心型插值法分析。与机器学习集的流程类似，同样是机器学习聚类降噪或者压缩的基本流程，前处理是做了一次平滑，为了尽量消除随机机器学习基于重心型插值拉格朗日重心型插值法分析面向数据生命周期的自适应访问控制方法算法样本引入的不确定性，这个过程同样依赖于带宽，也就是分类的数量。由于是平滑过程，比观察得到的样本数量小。拉格朗日重心型插值法应用领域有机械的设计和制作、还有计算机等方面，是一种比较实用的重心型。法应用到实际中,将算法在计算机中实现，时的实际意义。

关键词：重心型插值基函数 重心型插值多项式 Lagrange重心型插值 算法

Based on the Center of Gravity Type Interpolation Applied Research

Abstract

Abstract: interpolation method is to construct polynomial function through the two-dimensional plane several known point. As n polynomial center of gravity difference,Lagrange center of gravity type interpolation successfully solves the n polynomial center of gravity type interpolation function problem by constructing the center of gravity type interpolation basis function. The essential idea of Lagrange center of gravity interpolation is to write the NTH degree polynomial by other formulas, and determine the undetermined function by center of gravity interpolation conditions, and then calculate center of gravity interpolation polynomials.The estimation series structure machine learning f1 based on center of gravity interpolation Lagrangian method is post-processed, and the estimation series structure machine learning domain based on center of gravity interpolation Lagrangian method is re-transformed into X, and the f1 is converted into estimation series structure machine learning based on center of gravity interpolation Lagrangian method. It is the same as the machine learning set,and it is also the basic process of machine learning clustering noise reduction or compression. Pre-processing is a smoothing process. In order to eliminate the uncertainty introduced by random machine learning to analyze the sample of adaptive access control algorithm for data life cycle based on center of gravity interpolation Lagrange method, this process also depends on the bandwidth parameter nb, that is, the number of fractions.Because it is a smoothing process, nb is smaller than the number of samples observed.Lagrange center of gravity interpolation is a practical center of gravity interpolation method in the fields of fishery resource assessment, engineering and industry, Matlab, design and manufacture of machinery, as well as computer.This topic intends to apply Lagrange center of gravity interpolation method to practice.It is mainly through the programming (with Lagrange center of gravity interpolation method MATLAB implementation) algorithm in the computer to achieve the corresponding solution,and further reflects the practical significance of Lagrange center of gravity interpolation in solving the problem.

Keywords: center of gravity type interpolation basis function, center of gravity type interpolation polynomial,Lagrange center of gravity interpolation,algorithm

目录

摘要 2

Abstract 3

第一章 绪论 1

1.1 选题目的意义 1

1.2 国内外有关的研究动态 1

1.3 主要内容 4

1.4 研究方法 5

第二章 拉格朗日重心型插值法 6

2.1 拉格朗日插值公式的推导 6

2.2 拉格朗日重心型插值法 9

2.3余项与误差估计 13

第三章 拉格朗日重心型插值法的程序设计 16

3.1 拉格朗日重心型插值法的Matlab实现 16

第四章 重心插值在Allen-Cahn方程中的运用 19

4.1 Allen-Cahn方程 19

4.2 数值算法举例 20

第五章 Schwartz方法的生命周期阶段交叉验证 22

5.1 M-SEMAL 算法 22

5.2 阶段策略信息正则化特征提取 24

第六章 结论 26

参考文献 27

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