高等学校教材系列：线性代数及其应用（英文版）（第3版）

作者: [美] 莱著

出版社: 电子工业出版社

出版时间: 2004-01

版次: 1

ISBN: 9787505396258

定价: 49.00

装帧: 平装

开本: 其他

纸张: 胶版纸

页数: 112页

字数: 806千字

丛书: 高等学校教材

分类: 教材教辅考试>教材>大学教材>工程技术

8人买过

　　线性代数是处理矩阵和向量空间的数学分支科学，在现代数学的各个领域都有应用。本书主要包括线性方程组、矩阵代数、行列式、向量空间、特征值和特征向量、正交性和最小二乘方、对称矩阵和二次型等内容。本书的目的是使学生掌握线性代数最基本的概念、理论和证明。首先以常见的方式，具体介绍了线性独立、子空间、向量空间和线性变换等概念，然后逐渐展开，最后在抽象地讨论概念时，它们就变得容易理解多了。

　　这是一本介绍性的线性代数教材，内容翔实，层次清晰，适合作为高等院校理工科数学课的教学用书，还可作为公司职员及工程学研究人员的参考书。 David C.Lay：是一位教育家，发表过30余篇关于函数分析和线性代数的研究论文。他还是由美国国家科学基金会资助的线性代数课程研究小组的创始人。Lay参与编写了包括“Introduction to Functional Analysis”、“Calculus and Its Applications”和“Linear Algebra Gems-A CHAPTER 1 Linear Equations in Linear Algebra

INTRODUCTORY EXAMPLE:Linear Models in Economics and Engineering

1.1 Systems of Linear Equations

1.2 Row Reduction and Echelon Forms

1.3 Vector Equations

1.4 The Matrix Equation Ax=b

1.5 Solution Sets of Linear Systems

1.6 Applications of Linear Systems

1.7 Linear Independence

1.8 Introduction to Linear Transformations

1.9 The Matrix of a Linear Transformation

1.10 Linear Models in business,Science,and Engineering

      Supplementary Exercise

CHAPTER 2 Matrix Algebra

INTRODUCTORY EXAMPLE:Computer Models in Aircraft Design

2.1 Matrix Operations

2.2 The Inverse of a Matrix

2.3 Characterizations of Invertible Matrices

2.4 Partitioned Matrices

2.5 Matrix Factorizations

2.6 The Leontief Input-Output Model

2.7 Applications to Computer Graphics

2.8 Subspaces of Rn

2.9 Dimension and Rank

     Supplementary Exercise

CHAPTER 3 Determinants

INTRODUCTORY EXAMPLE:Determinants in Analytic Geometry

3.1 Introduction to Determinants

3.2 Properties of Determinants

3.3 Cramer's Rule,Volume,and Linear Transformations

     Supplementary Exercise

CHAPTER 4 Vector Spaces

INTRODUCTORY EXAMPLE:Space Flight and Control Systems

4.1 Vector Spaces and Subspaces

4.2 Null Spaces,Column Spaces,and Linear Transformations

4.3 Linearly Independent Sets;Bases

4.4 Coordinate Systems

4.5 The Dimension of a Vector Space

4.6 Rank

4.7 Change of Basis

4.8 Applications to Difference Equations

4.9 Applications to Markov Chains

     Supplementary Exercise

CHAPTER 5 Eigenvalues and Eigenvectors

INTRODUCTORY EXAMPLE:Dynamical Systems

5.1 Eigenvectors and Eigenvalues

5.2 The Characteristic Equation

5.3 Diagonalization

5.4 Eigenvectors and Linear Transformations

5.5 Complex Eigenvalues

5.6 Discrete Dynamical Systems

5.7 Applications to Differential Equations

5.8 Iterative Estimates for Eigenvalues

     Supplementary Exercise

CHAPTER 6 Orthogonality and Least Squares

INTRODUCTORY EXAMPLE:Readjusting the North American Datum

6.1 Inner Product,Length,and Orthogonality

6.2 Orthogonal Sets

6.3 Orthogonal Projections

6.4 The Gram-Schmidt Process

6.5 Least-Squares Problems

6.6 Applications to Linear Models

6.7 Inner Product Spaces

6.8 Applications of Inner Product Spaces

     Supplementary Exercise

CHAPTER 7 Symmetric Matrices and Quadratic Forms

INTRODUCTORY EXAMPLE:Multichannel Image Processing

7.1 Diagonalization of Symmetric Matrices

7.2 Quadratic Forms

7.3 Constrained Optimization

7.4 The Singular Value Decomposition

7.5 Applications to Image Processing and Statistics

     Supplementary Exercise

Appendixes

A Uniqueness of the Reduced Echelon Form

B Complex Numbers

Glossary

Answers to Odd-Numbered Exercises

Index
内容简介:
　　线性代数是处理矩阵和向量空间的数学分支科学，在现代数学的各个领域都有应用。本书主要包括线性方程组、矩阵代数、行列式、向量空间、特征值和特征向量、正交性和最小二乘方、对称矩阵和二次型等内容。本书的目的是使学生掌握线性代数最基本的概念、理论和证明。首先以常见的方式，具体介绍了线性独立、子空间、向量空间和线性变换等概念，然后逐渐展开，最后在抽象地讨论概念时，它们就变得容易理解多了。

　　这是一本介绍性的线性代数教材，内容翔实，层次清晰，适合作为高等院校理工科数学课的教学用书，还可作为公司职员及工程学研究人员的参考书。
作者简介:
David C.Lay：是一位教育家，发表过30余篇关于函数分析和线性代数的研究论文。他还是由美国国家科学基金会资助的线性代数课程研究小组的创始人。Lay参与编写了包括“Introduction to Functional Analysis”、“Calculus and Its Applications”和“Linear Algebra Gems-A
目录:
CHAPTER 1 Linear Equations in Linear Algebra

INTRODUCTORY EXAMPLE:Linear Models in Economics and Engineering

1.1 Systems of Linear Equations

1.2 Row Reduction and Echelon Forms

1.3 Vector Equations

1.4 The Matrix Equation Ax=b

1.5 Solution Sets of Linear Systems

1.6 Applications of Linear Systems

1.7 Linear Independence

1.8 Introduction to Linear Transformations

1.9 The Matrix of a Linear Transformation

1.10 Linear Models in business,Science,and Engineering

      Supplementary Exercise

CHAPTER 2 Matrix Algebra

INTRODUCTORY EXAMPLE:Computer Models in Aircraft Design

2.1 Matrix Operations

2.2 The Inverse of a Matrix

2.3 Characterizations of Invertible Matrices

2.4 Partitioned Matrices

2.5 Matrix Factorizations

2.6 The Leontief Input-Output Model

2.7 Applications to Computer Graphics

2.8 Subspaces of Rn

2.9 Dimension and Rank

     Supplementary Exercise

CHAPTER 3 Determinants

INTRODUCTORY EXAMPLE:Determinants in Analytic Geometry

3.1 Introduction to Determinants

3.2 Properties of Determinants

3.3 Cramer's Rule,Volume,and Linear Transformations

     Supplementary Exercise

CHAPTER 4 Vector Spaces

INTRODUCTORY EXAMPLE:Space Flight and Control Systems

4.1 Vector Spaces and Subspaces

4.2 Null Spaces,Column Spaces,and Linear Transformations

4.3 Linearly Independent Sets;Bases

4.4 Coordinate Systems

4.5 The Dimension of a Vector Space

4.6 Rank

4.7 Change of Basis

4.8 Applications to Difference Equations

4.9 Applications to Markov Chains

     Supplementary Exercise

CHAPTER 5 Eigenvalues and Eigenvectors

INTRODUCTORY EXAMPLE:Dynamical Systems

5.1 Eigenvectors and Eigenvalues

5.2 The Characteristic Equation

5.3 Diagonalization

5.4 Eigenvectors and Linear Transformations

5.5 Complex Eigenvalues

5.6 Discrete Dynamical Systems

5.7 Applications to Differential Equations

5.8 Iterative Estimates for Eigenvalues

     Supplementary Exercise

CHAPTER 6 Orthogonality and Least Squares

INTRODUCTORY EXAMPLE:Readjusting the North American Datum

6.1 Inner Product,Length,and Orthogonality

6.2 Orthogonal Sets

6.3 Orthogonal Projections

6.4 The Gram-Schmidt Process

6.5 Least-Squares Problems

6.6 Applications to Linear Models

6.7 Inner Product Spaces

6.8 Applications of Inner Product Spaces

     Supplementary Exercise

CHAPTER 7 Symmetric Matrices and Quadratic Forms

INTRODUCTORY EXAMPLE:Multichannel Image Processing

7.1 Diagonalization of Symmetric Matrices

7.2 Quadratic Forms

7.3 Constrained Optimization

7.4 The Singular Value Decomposition

7.5 Applications to Image Processing and Statistics

     Supplementary Exercise

Appendixes

A Uniqueness of the Reduced Echelon Form

B Complex Numbers

Glossary

Answers to Odd-Numbered Exercises

Index

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高等学校教材系列：线性代数及其应用（英文版）（第3版）

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