0去购物车结算
购物车中还没有商品,赶紧选购吧!
当前位置: 图书分类 > 数学 > 计算数学 > 散乱数据拟合的模型、方法和理论(第二版)(英文版)

相同语种的商品

浏览历史

散乱数据拟合的模型、方法和理论(第二版)(英文版)


联系编辑
 
标题:
 
内容:
 
联系方式:
 
  
散乱数据拟合的模型、方法和理论(第二版)(英文版)
  • 书号:9787030748553
    作者:吴宗敏
  • 外文书名:
  • 装帧:平装
    开本:B5
  • 页数:176
    字数:250000
    语种:en
  • 出版社:科学出版社
    出版时间:2023-03-01
  • 所属分类:
  • 定价: ¥98.00元
    售价: ¥77.42元
  • 图书介质:
    纸质书

  • 购买数量: 件  可供
  • 商品总价:

相同系列
全选

内容介绍

样章试读

用户评论

全部咨询

本书是应用数学与计算数学中有关曲面及多元函数插值、逼近、拟合的入门书籍,从多种物理背景、原理出发,导出相应的散乱数据拟合的数学模型及计算方法,进而逐个进行深入的理论分析。书中介绍了多元散乱数据拟合的一般方法,包括多元散乱数据多项式插值、基于三角剖分的插值方法、Boole和与Coons曲面、Sibson方法或自然邻近法、Shepard方法、Kriging方法、薄板样条方法、MQ拟插值法、径向基函数方法、运动最小二乘法、隐函数样条方法、R函数法等;同时还特别介绍了近年来国际上越来越热并在无网格微分方程数值解方面有诸多应用的径向基函数方法及其相关理论。
样章试读
  • 暂时还没有任何用户评论
总计 0 个记录,共 1 页。 第一页 上一页 下一页 最末页

全部咨询(共0条问答)

  • 暂时还没有任何用户咨询内容
总计 0 个记录,共 1 页。 第一页 上一页 下一页 最末页
用户名: 匿名用户
E-mail:
咨询内容:

目录

  • Contents
    Preface to the Second Edition Preface to the First Edition
    Chapter 1 Scattered Data Approximation and Multivariate Polynomial Interpolation 1
    1.1 Motivation Problems 1
    1.1.1 Problems from Applications 2
    1.1.2 Problems from Mathematics 3
    1.2 Haar Condition for Interpolation 4
    1.3 Multivariate Polynomial Interpolation for Scattered Data 6
    1.3.1 Aitken Formula for Multivariate Interpolation 8
    1.3.2 Newton Formula for Multivariate Polynomial Interpolation 8
    Chapter 2 Local Methods 10
    2.1 Triangulation and Function Representation on a Triangle 10
    2.2 Smooth Connection Methods Based on Triangulation 17
    2.2.1 Linear Interpolation and Piecewise Linear Interpolation 17
    2.2.2 Nine-Parameter Cubic Method 18
    2.2.3 Clough-Tocher Method 20
    2.2.4 Powell-Sabin Method 21
    2.3 Boole and Coons Patches 23
    2.4 Subdivision Methods for Scattered Data Approximation 26
    2.4.1 Chaikin Method 27
    2.4.2 Doo-Sabin Method 29
    2.4.3 Four-Point Method 30
    2.4.4 Butterfly Algorithm 32
    2.5 Sibson Interpolation or Natural Proximity 33
    2.5.1 Scattered Data Interpolation with Lipschitz Constant Diminishing Property 36
    2.5.2 Convergence Theorem of Sibson Interpolation 39
    2.5.3 Interpolation Convergence Theorem for Interpolation with Lipschitz Constant Diminishing Property 39
    2.6 Shepard Method 40
    2.6.1 Shepard Interpolation with Derivative Information 42
    2.6.2 Generalization of Shepard Method 43
    Chapter 3 Global Methods 44
    3.1 Random Function Preliminary 44
    3.2 Kriging Method 48
    3.2.1 Inverse of Univariate Markov Type Correlation Matrix 51
    3.2.2 The Solution to Kriging Problem with Univariate Gaussian Type
    Correlation Matrix 52
    3.2.3 Monotonicity and Boundedness of Kriging Interpolation Operator 53
    3.2.4 Condition Number of Correlation Matrix 53
    3.3 Universal Kriging 54
    3.4 Co-Kriging 58
    3.4.1 Nugget Effect of Interpolation Operator 60
    3.4.2 Application of Co-Kriging on Hermite Interpolation 61
    3.5 Interpolation for Generalized Linear Functionals 62
    3.6 Splines 66
    3.7 Multi-Quadric Methods 73
    3.8 MQ Quasi-interpolation for Higher Order Derivative Approximation 84
    3.9 Stability for Derivative Approximation with FD and MQ 89
    3.10 Radial Basis Functions 94
    3.10.1 Radial Basis Function Interpolation 95
    3.10.2 Existence of Radial Basis Function Interpolation 95
    Chapter 4 Theory on Radial Basis Function Interpolation 99
    4.1 Convergence and Convergence Rate 99
    4.1.1 Quasi-Interpolation, Strang-Fix Condition and Shift Invariant Space 99
    4.2 Convergence Results for Scattered Data Radial Basis Function Interpolation 104
    4.2.1 Error Estimation 108
    4.2.2 Construction of Admissible Vectors 109
    4.3 Positive Definite Radial Basis Functions 112
    4.4 Bodmer Theory for Radial Basis Functions 119
    4.5 Radial Functions and Strang-Fix Conditions 126
    Chapter 5 Other Scattered Data Interpolation Methods 139
    5.1 Moving Least Squares 139
    5.1.1 Least Squares 139
    5.1.2 Moving Least Squares 140
    5.1.3 Interpolating Moving Least Squares Methods 141
    5.1.4 Divide and Conquer on General Domain 146
    5.2 Convergence Analysis of Shepard Methods 147
    5.2.1 Convergence Analysis for the Shepard Method 148
    5.3 Implicit Splines 154
    5.3.1 Other Scattered Data Interpolation Methods 157
    5.4 Partition of Unity 158
    5.5 R-function 159
    Chapter 6 Scatter Data Interpolation for Numerical Solutions of PDEs 161
    6.1 Generalized Functional Interpolations and Numerical Methods for PDEs 161
    6.2 Other Multivariate Approximation Methods for PDEs 168
    6.2.1 Least Squares Methods 169
    6.2.2 Collocation 170
    6.2.3 Galerkin Method 171
    6.2.4 Golberg Method 172
    Bibliography 173
帮助中心
公司简介
联系我们
常见问题
新手上路
发票制度
积分说明
购物指南
配送方式
配送时间及费用
配送查询说明
配送范围
快递查询
售后服务
退换货说明
退换货流程
投诉或建议
版权声明
经营资质
营业执照
出版社经营许可证