内容简介
《欧氏空间上的勒贝格积分(修订版)(英文版)》简明、详细地介绍勒贝格测度和Rn上的积分。《欧氏空间上的勒贝格积分(英文版)》的基本目的有四个,介绍勒贝格积分;从一开始引入n维空间;彻底介绍傅里叶积分;深入讲述实分析。贯穿全书的大量练习可以增强读者对知识的理解。目次:Rn导论;Rn勒贝格测度;勒贝格积分的不变性;一些有趣的集合;集合代数和可测函数;积分;Rn勒贝格积分;Rn的Fubini定理;Gamma函数;Lp空间;抽象测度的乘积;卷积;Rn+上的傅里叶变换;单变量傅里叶积分;微分;R上函数的微分。
读者对象:《欧氏空间上的勒贝格积分(修订版)(英文版)》适用于数学专业的学生、老师和相关的科研人员。
内页插图
目录
Preface
Bibliography
Acknowledgments
1 Introduction to Rn
A Sets
B Countable Sets
C Topology
D Compact Sets
E Continuity
F The Distance Function
2 Lebesgue Measure on Rn
A Construction
B Properties of Lebesgue Measure
C Appendix: Proof of P1 and P2
3 Invariance of Lebesgue Measure
A Some Linear Algebra
B Translation and Dilation
C Orthogonal Matrices
D The General Matrix
4 Some Interesting Sets
A A Nonmeasurable Set
B A Bevy of Cantor Sets
C The Lebesgue Function
D Appendix: The Modulus of Continuity of the Lebesgue Functions
5 Algebras of Sets and Measurable Functions
A Algebras and a-Algebras
B Borel Sets
C A Measurable Set which Is Not a Borel Set
D Measurable Functions
E Simple Functions
6 Integration
A Nonnegative Functions
B General Measurable Functions
C Almost Everywhere
D Integration Over Subsets of Rn
E Generalization: Measure Spaces
F Some Calculations
G Miscellany
7 Lebesgue Integral on Rn
A Riemann Integral
B Linear Change of Variables
C Approximation of Functions in L1
D Continuity of Translation in L1
8 Fubinis Theorem for Rn
9 The Gamma Function
A Definition and Simple Properties
B Generalization
C The Measure of Balls
D Further Properties of the Gamma Function
E Stirlings Formula
F The Gamma Function on R
10 LP Spaces ,
A Definition and Basic Inequalities
B Metric Spaces and Normed Spaces
C Completeness of Lp
D The Case p=∞
E Relations between Lp Spaces
F Approximation by C∞c (Rn)
G Miscellaneous Problems ;
H The Case 0[p[1
11 Products of Abstract Measures
A Products of 5-Algebras
B Monotone Classes
C Construction of the Product Measure
D The Fubini Theorem
E The Generalized Minkowski Inequality
12 Convolutions
A Formal Properties
B Basic Inequalities
C Approximate Identities
13 Fourier Transform on Rn
A Fourier Transform of Functions in L1 (Rn)
B The Inversion Theorem
C The Schwartz Class
D The Fourier-Plancherel Transform
E Hilbert Space
F Formal Application to Differential Equations
G Bessel Functions
H Special Results for n = i
I Hermite Polynomials
14 Fourier Series in One Variable
A Periodic Functions
B Trigonometric Series
C Fourier Coefficients
D Convergence of Fourier Series
E Summability of Fourier Series
F A Counterexample
G Parsevals Identity
H Poisson Summation Formula
I A Special Class of Sine Series
15 Differentiation
A The Vitali Covering Theorem
B The Hardy-Littlewood Maximal Function
C Lebesgues Differentiation Theorem
D The Lebesgue Set of a Function
E Points of Density
F Applications
G The Vitali Covering Theorem (Again)
H The Besicovitch Covering Theorem
I The Lebesgue Set of Order p
J Change of Variables
K Noninvertible Mappings
16 Differentiation for Functions on R
A Monotone Functions
B Jump Functions
C Another Theorem of Fubini
D Bounded Variation
E Absolute Continuity
F Further Discussion of Absolute Continuity
G Arc Length
H Nowhere Differentiable Functions
I Convex Functions
Index
Symbol Index
前言/序言
"Though of real knowledge there be little, yet of books there are plenty" -Herman Melville, Moby Dick, Chapter XXXI.
The treatment of integration developed by the French mathematician Henri Lebesgue (1875-1944) almost a century ago has proved to be indispensable in many areas of mathematics. Lebesgues theory is of such extreme importance because on the one hand it has rendered previous theories of integration virtually obsolete, and on the other hand it has not been replaced with a significantly different, better theory. Most subsequent important investigations of integration theory have extended or illuminated Lebesgues work.
In fact, as is so often the case in a new field of mathematics, many of the best consequences were given by the originator. For example,Lebesgues dominated convergence theorem, Lebesgues increasing convergence theorem, the theory of the Lebesgue function of the Cantor ternary set, and Lebesgues theory of differentiation of indefinite integrals.
Naturally, many splendid textbooks have been produced in this area.I shall list some of these below. They axe quite varied in their approach to the subject. My aims in the present book are as follows.
1. To present a slow introduction to Lebesgue integration Most books nowadays take the opposite tack. I have no argument with their approach, except that I feel that many students who see only a very rapid approach tend to lack strong intuition about measure and integration. That is why I have made Chapter 2, "Lebesgue measure on Rn,"so lengthy and have restricted it to Euclidean space, and why I have (somewhat inconveniently) placed Chapter 3, "Invaxiance of Lebesgue measure," before Pubinis theorem. In my approach I have omitted much important material, for the sake of concreteness. As the title of the book signifies, I restrict attention almost entirely to Euclidean space.
2. To deal with n-dimensional spaces from the outset. I believe this is preferable to one standard approach to the theory which first thoroughly treats integration on the real line and then generalizes. There are several reasons for this belief. One is quite simply that significant figures are frequently easier to sketch in IRe than in R1! Another is that some things in IR1 are so special that the generalization to Rn is not clear; for example, the structure of the most general open set in R1 is essentially trivial —— it must be a disjoint union of open intervals (see Problem 2.6). A third is that coping with the n-dimensional case from the outset causes the learner to realize that it is not significantly more difficult than the one-dimensional case as far as many aspects of integration are concerned.
3. To provide a thorough treatment of Fourier analysis. One of the triumphs of Lebesgue integration is the fact that it provides definitive answers to many questions of Fourier analysis. I feel that without a thorough study of this topic the student is simply not well educated in integration theory. Chapter 13 is a very long one on the Fourier transform in several variables, and Chapter 14 also a very long one on Fourier series in one variable.
测度论与泛函分析基础 专著简介 本书系统地阐述了现代数学分析的两大核心支柱:测度论(Measure Theory)与泛函分析(Functional Analysis)的基石概念、基本定理及其在解决经典分析问题中的应用。全书结构严谨,逻辑清晰,旨在为读者构建一个从拓扑基础到高级抽象结构的坚实桥梁,尤其适合数学、物理及相关工程领域的高年级本科生、研究生以及希望深化理论基础的研究人员。 全书共分为四个主要部分,内容层层递进,深入浅出。 --- 第一部分:拓扑预备与集合论基础(Foundations of Topology and Set Theory) 本部分首先回顾和深化了读者对点集拓扑的理解,为后续的测度论奠定必要的空间结构基础。我们从一般拓扑空间的概念出发,详细讨论了开集、闭集、紧致性(Compactness)、连通性(Connectedness)以及完备性(Completeness)等核心性质。 内容提要: 1. 拓扑空间的构造: 引入度量空间(Metric Spaces)作为具体的模型,探讨开球、闭球的性质,并推广到更一般的拓扑空间定义。重点分析了Hausdorff空间和完备度量空间(如Baire空间)的特性。 2. 函数空间拓扑: 讨论函数空间的常见拓扑结构,包括逐点收敛、一致收敛以及各种泛函分析中将扮演关键角色的拓扑概念(如紧开收敛)。 3. 可数紧致性与Borel集: 紧致性在分析中的重要性不言而喻。本章将深入探讨可数紧致性与序列紧致性之间的关系,并详述Borel $sigma$-代数(Borel $sigma$-algebra)的构造,这是定义测度的起点。我们精确地界定了在任何拓扑空间上,由开集生成的最小 $sigma$-代数及其重要性质。 --- 第二部分:测度论的构建(Construction of Measure Theory) 本部分是全书的核心基础,专注于测度论的严格构建,从外部测度(Outer Measure)过渡到 $sigma$-有限测度($sigma$-Finite Measures),并详细介绍了勒贝格测度的构造过程。 内容提要: 1. Carathéodory扩张定理: 这是测度论的基石。我们将从一个给定的外部测度出发,系统地构建可测集族(Measurable Sets)和对应的测度函数。详细分析了 $sigma$-可加性($sigma$-Additivity)和有限可加性之间的本质区别。 2. $sigma$-有限测度的性质: 讨论了 $sigma$-有限测度的定义及其在测度论中的特殊地位。我们将分析有限测度空间(Finite Measure Spaces)和 $sigma$-有限测度空间下的基本结构定理。 3. 乘积测度与Fubini定理的先导: 在建立单变量积分之前,本章引入了乘积空间的直观概念,并为后续的Fubini和Tonelli定理的严格证明打下基础。虽然本部分不深入多维积分,但会清晰展示如何通过Kolmogorov扩张原理构造乘积测度,这对于理解更高维度积分至关重要。 4. 有界函数与积分的定义: 详细定义了简单函数(Simple Functions)和非负可测函数。通过递增逼近原理,严格定义了勒贝格积分(Lebesgue Integral)的概念,并探讨了积分的单调性与连续性性质。 --- 第三部分:积分的深入研究与收敛性(Advanced Integration and Convergence Theorems) 本部分将积分的理论提升到更高的层次,重点研究各种收敛定理,它们是微积分中极限和积分顺序交换的严格数学基础。 内容提要: 1. 三大收敛定理的证明与应用: 本章对测度论中最著名的三个定理——单调收敛定理(Monotone Convergence Theorem, MCT)、法图勒引理(Fatou's Lemma)和占优收敛定理(Dominated Convergence Theorem, DCT)——进行了详尽的证明和对比。特别强调了DCT在处理积分与微分关系时的强大威力。 2. $L^p$ 空间(Lebesgue Spaces): 严格定义 $L^p$ 空间,并分析其作为赋范向量空间的基本属性。 Hölder不等式与Minkowski不等式: 对 $L^p$ 空间上的乘积进行估计,证明了这些关键不等式的等价形式及其在分析中的应用。 完备性: 证明 $L^p$ 空间(对于 $p ge 1$)是完备的巴拿赫空间,这是泛函分析的基础。 3. 积分的绝对连续性与Radon-Nikodym定理的铺垫: 探讨积分与测度的关系,引入绝对连续测度(Absolutely Continuous Measures)的概念,为后续的微分与积分关系(Radon-Nikodym导数)做好铺垫。 --- 第四部分:泛函分析的引言(Introduction to Functional Analysis) 本部分将测度论的成果应用于抽象的函数空间,开启了泛函分析的大门。重点关注线性算子、拓扑向量空间以及对偶空间的概念。 内容提要: 1. 拓扑向量空间(Topological Vector Spaces): 将向量空间的线性结构与拓扑结构结合起来。讨论局部凸性(Local Convexity)和常见的拓扑结构(如 $|cdot|_p$ 范数下的结构)。 2. 巴拿赫空间与希尔伯特空间(Banach and Hilbert Spaces): 集中讨论完备的赋范向量空间。 希尔伯特空间: 引入内积概念,探讨闭凸集上的投影定理,这是变分法和优化理论的基石。 Riesz表示定理的初步介绍: 阐述了希尔伯特空间中线性泛函的表示形式,这是连接几何结构与代数结构的关键桥梁。 3. 有界线性算子(Bounded Linear Operators): 定义算子的范数,并研究算子空间的拓扑结构。 4. Hahn-Banach定理的叙述与几何意义: 阐述分离超平面定理(Separation Hyperplane Theorem)的函数空间版本——Hahn-Banach扩张定理,并讨论其在构造分离泛函方面的关键作用,这是理解对偶空间结构的重要一步。 本书的结构旨在让读者在掌握了严格的测度论工具后,能够自然地步入泛函分析的抽象世界,为处理偏微分方程、调和分析和概率论中的高级问题做好充分准备。全书的论证力求细致入微,确保读者能够独立地理解每一个理论推导的每一步。