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 Exercises

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 Exercises

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 Exercises

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 Exercises

CHAPTER 5　Eigenvalues and Eigenvectors

INTRODUCTORY EXAMPLE:Dynamical Systems and Spotted Owls

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 Exercises

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 Exercises

CHAPTER 7　SVmmetric 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 Exercises