An Introduction to Linear Algebra

Name: An Introduction to Linear Algebra
Brand: EDP sciences
Price: 185.77 EUR
Availability: OnlineOnly

Xuan Liu Zhi ZHAO Wei-Hui LIU Xiao-Qing Jin(Autor*in)

EDP sciences (Verlag)

Erschienen am 8. Dezember 2022

236 Seiten

E-Book

PDF mit Adobe-DRM

Systemvoraussetzungen

978-2-7598-3045-9 (ISBN)

185,77 €inkl. 7% MwSt.

Systemvoraussetzungen

für PDF mit Adobe-DRM

E-Book Einzellizenz

Als Download verfügbar

Beschreibung

Weitere Details

Personen

Inhalt

Cover-1
Cover-2
An Introduction to Linear Algebra
Preface
Contents
Chapter 1 Linear Systems and Matrices
1.1 Introduction to Linear Systems and Matrices
1.1.1 Linear equations and linear systems
1.1.2 Matrices
1.1.3 Elementary row operations
1.2 Gauss-Jordan Elimination
1.2.1 Reduced row-echelon form
1.2.2 Gauss-Jordan elimination
1.2.3 Homogeneous linear systems
1.3 Matrix Operations
1.3.1 Operations on matrices
1.3.2 Partition of matrices
1.3.3 Matrix product by columns and by rows
1.3.4 Matrix product of partitioned matrices
1.3.5 Matrix form of a linear system
1.3.6 Transpose and trace of a matrix
1.4 Rules of Matrix Operations and Inverses
1.4.1 Basic properties of matrix operations
1.4.2 Identity matrix and zero matrix
1.4.3 Inverse of a matrix
1.4.4 Powers of a matrix
1.5 Elementary Matrices and a Method for Finding A-1
1.5.1 Elementary matrices and their properties
1.5.2 Main theorem of invertibility
1.5.3 A method for finding A-1
1.6 Further Results on Systems and Invertibility
1.6.1 A basic theorem
1.6.2 Properties of invertible matrices
1.7 Some Special Matrices
1.7.1 Diagonal and triangular matrices
1.7.2 Symmetric matrix
Exercises
Chapter 2 Determinants
2.1 Determinant Function
2.1.1 Permutation, inversion, and elementary product
2.1.2 Definition of determinant function
2.2 Evaluation of Determinants
2.2.1 Elementary theorems
2.2.2 A method for evaluating determinants
2.3 Properties of Determinants
2.3.1 Basic properties
2.3.2 Determinant of a matrix product
2.3.3 Summary
2.4 Cofactor Expansions and Cramer's Rule
2.4.1 Cofactors
2.4.2 Cofactor expansions
2.4.3 Adjoint of a matrix
2.4.4 Cramer's rule
Exercises
Chapter 3 Euclidean Vector Spaces
3.1 Euclidean n-Space
3.1.1 n-vector space
3.1.2 Euclidean n-space
3.1.3 Norm, distance, angle, and orthogonality
3.1.4 Some remarks
3.2 Linear Transformations from Rn to Rm
3.2.1 Linear transformations from Rn to Rm
3.2.2 Some important linear transformations
3.2.3 Compositions of linear transformations
3.3 Properties of Transformations
3.3.1 Linearity conditions
3.3.2 Example
3.3.3 One-to-one transformations
3.3.4 Summary
Exercises
Chapter 4 General Vector Spaces
4.1 Real Vector Spaces
4.1.1 Vector space axioms
4.1.2 Some properties
4.2 Subspaces
4.2.1 Definition of subspace
4.2.2 Linear combinations
4.3 Linear Independence
4.3.1 Linear independence and linear dependence
4.3.2 Some theorems
4.4 Basis and Dimension
4.4.1 Basis for vector space
4.4.2 Coordinates
4.4.3 Dimension
4.4.4 Some fundamental theorems
4.4.5 Dimension theorem for subspaces
4.5 Row Space, Column Space, and Nullspace
4.5.1 Definition of row space, column space, and nullspace
4.5.2 Relation between solutions of Ax = 0 and Ax = b
4.5.3 Bases for three spaces
4.5.4 A procedure for finding a basis for span(S)
4.6 Rank and Nullity
4.6.1 Rank and nullity
4.6.2 Rank for matrix operations
4.6.3 Consistency theorems
4.6.4 Summary
Exercises
Chapter 5 Inner Product Spaces
5.1 Inner Products
5.1.1 General inner products
5.1.2 Examples
5.2 Angle and Orthogonality
5.2.1 Angle between two vectors and orthogonality
5.2.2 Properties of length, distance, and orthogonality
5.2.3 Complement
5.3 Orthogonal Bases and Gram-Schmidt Process
5.3.1 Orthogonal and orthonormal bases
5.3.2 Projection theorem
5.3.3 Gram-Schmidt process
5.3.4 QR-decomposition
5.4 Best Approximation and Least Squares
5.4.1 Orthogonal projections viewed as approximations
5.4.2 Least squares solutions of linear systems
5.4.3 Uniqueness of least squares solutions
5.5 Orthogonal Matrices and Change of Basis
5.5.1 Orthogonal matrices
5.5.2 Change of basis
Exercises
Chapter 6 Eigenvalues and Eigenvectors
6.1 Eigenvalues and Eigenvectors
6.1.1 Introduction to eigenvalues and eigenvectors
6.1.2 Two theorems concerned with eigenvalues
6.1.3 Bases for eigenspaces
6.2 Diagonalization
6.2.1 Diagonalization problem
6.2.2 Procedure for diagonalization
6.2.3 Two theorems concerned with diagonalization
6.3 Orthogonal Diagonalization
6.4 Jordan Decomposition Theorem
Exercises
Chapter 7 Linear Transformations
7.1 General Linear Transformations
7.1.1 Introduction to linear transformations
7.1.2 Compositions
7.2 Kernel and Range
7.2.1 Kernel and range
7.2.2 Rank and nullity
7.2.3 Dimension theorem for linear transformations
7.3 Inverse Linear Transformations
7.3.1 One-to-one and onto linear transformations
7.3.2 Inverse linear transformations
7.4 Matrices of General Linear Transformations
7.4.1 Matrices of linear transformations
7.4.2 Matrices of compositions and inverse transformations
7.5 Similarity
Exercises
Chapter 8 Additional Topics
8.1 Quadratic Forms
8.1.1 Introduction to quadratic forms
8.1.2 Constrained extremum problem
8.1.3 Positive definite matrix
8.2 Three Theorems for Symmetric Matrices
8.3 Complex Inner Product Spaces
8.3.1 Complex numbers
8.3.2 Complex inner product spaces
8.4 Hermitian Matrices and Unitary Matrices
8.5 Böttcher-Wenzel Conjecture
8.5.1 Introduction
8.5.2 Proof of the Böttcher-Wenzel conjecture
Exercises
Appendix A Independence of Axioms
Bibliography
Index

Systemvoraussetzungen

Als PDF speichern Als Link merken