LA
Nguồn ngoài
Linear Algebra with Applications
The aim of the textbook is to achieve a balance among computational skills, theory, and applications of linear algebra. It is a relatively advanced introduction to the ideas and techniques of linear algebra targeted for science and engineering students who need to understand not only how to use these methods but also gain insight into why they work. The contents have enough flexibility to present a traditional introduction to the subject, or to allow for a more applied course.
- Tác giả
- W. Keith Nicholson
- Nhà xuất bản
- University of Calgary
- Nguồn
- LibreTexts
- Giấy phép
- CC BY-NC-SA
- Ngôn ngữ
- EN
- Danh mục
- Khoa học cơ bản
Mục lục· 167 mục
- 01: Systems of Linear Equations
- 1.00: Prelude to Systems of Linear Equations
- 1.01: Solutions and Elementary Operations
- 1.1E: Exercises for Section 1.1
- 1.02: Gaussian Elimination
- 1.2E: Solutions and Elementary Operations Exercises
- 1.03: Homogeneous Equations
- 1.3E: Homogeneous Equations
- 1.04: An Application to Network Flow
- 1.4E: An Application to Network Flow Exercises
- 1.05: An Application to Electrical Networks
- 1.5E: An Application to Electrical Networks Exercises
- 1.06: An Application to Chemical Reactions
- 1.6E: An Application to Chemical Reactions Exercises
- 1.E: Supplementary Exercises for Chapter 1
- 02: Matrix Algebra
- 2.00: Prelude to Matrix Algebra
- 2.01: Matrix Addition Scalar Multiplication and Transposition
- 2.1E: Matrix Addition Scalar Multiplication and Transposition Exercises
- 2.02: Equations Matricies and Transformations
- 2.2E: Matrix-Vector Multiplication Exercises
- 2.03: Matrix Multiplication
- 2.3E: Matrix Multiplication Exercises
- 2.04: Matrix Inverses
- 2.4E: Matrix Inverses Exercises
- 2.05: Elementary Matrices
- 2.5E: Elementary Matrices Exercises
- 2.06: Linear Transformations
- 2.6E: Linear Transformations Exercises
- 2.07: LU-Factorization
- 2.7E: LU-Factorization Exercises
- 2.08: An Application to Input-Output Economic Models
- 2.8E: An Application to Input-Output Economic Models Exercises
- 2.09: An Application to Markov Chains
- 2.9E: An Application to Markov Chains Exercises
- 2.E: Supplementary Exercises for Chapter 2
- 03: Determinants and Diagonalization
- 3.00: Prelude to Determinants and Diagonalization
- 3.01: The Cofactor Expansion
- 3.1E: The Cofactor Expansion Exercises
- 3.02: Determinants and Matrix Inverses
- 3.2E: Determinants and Matrix Inverses Exercises
- 3.03: Eigenvalues and Eigenvectors
- 3.3E: Eigenvalues and Eigenvectors Exercises
- 3.04: Diagonalization
- 3.4E: Diagonalization Exercises
- 3.05: Linear Dynamical Systems
- 3.5E: Linear Dynamical Systems Exercises
- 3.06: An Application to Linear Recurrences
- 3.6E: An Application to Linear Recurrences Exercises
- 3.07: An Application to Systems of Differential Equations
- 3.7E: An Application to Systems of Differential Equations Exercises
- 3.08: Proof of the Cofactor Expansion Theorem
- 3.8E: Proof of the Cofactor Expansion Theorem Exercises
- 3.E: Supplementary Exercises for Chapter 3
- 04: Vector Geometry
- 4.00: Prelude to Vector Geometry
- 4.01: Vectors and Lines
- 4.1E: Vectors and Lines Exercises
- 4.02: Projections and Planes
- 4.2E: Projections and Planes Exercises
- 4.03: More on the Cross Product
- 4.3E: More on the Cross Product Exercises
- 4.04: Linear Operators on R
- 4.4E: Linear Operators on R Exercises
- 4.05: An Application to Computer Graphics
- 4.5E: An Application to Computer Graphics Exercises
- 4.E: Supplementary Exercises for Chapter 4
- 05: Vector Space R
- 5.00: Prelude to Vector Space R
- 5.01: Subspaces and Spanning
- 5.1E: Subspaces and Spanning Exercises
- 5.02: Independence and Dimension
- 5.2E: Independence and Dimension Exercises
- 5.03: Orthogonality
- 5.3E: Orthogonality Exercises
- 5.04: Rank of a Matrix
- 5.4E: Rank of a Matrix Exercises
- 5.05: Similarity and Diagonalization
- 5.5E: Similarity and Diagonalization Exercises
- 5.06: Best Approximation and Least Squares
- 5.6E: Best Approximation and Least Squares Exercises
- 5.07: An Application to Correlation and Variance
- 5.7E: An Application to Correlation and Variance Exercises
- 5.E: Supplementary Exercises for Chapter 5
- 06: Vector Spaces
- 6.00: Prelude to Vector Spaces
- 6.01: Examples and Basic Properties
- 6.1E: Examples and Basic Properties Exercises
- 6.02: Subspaces and Spanning Sets
- 6.2E: Subspaces and Spanning Sets Exercises
- 6.03: Linear Independence and Dimension
- 6.3E: Linear Independence and Dimension Exercises
- 6.04: Finite Dimensional Spaces
- 6.4E: Finite Dimensional Spaces Exercises
- 6.05: An Application to Polynomials
- 6.5E: An Application to Polynomials Exercises
- 6.06: An Application to Differential Equations
- 6.6E: An Application to Differential Equations Exercises
- 6.E: Supplementary Exercises for Chapter 6
- 07: Linear Transformations
- 7.00: Prelude to Linear Transformations
- 7.01: Examples and Elementary Properties
- 7.1E: Examples and Elementary Properties Exercises
- 7.02: Kernel and Image of a Linear Transformation
- 7.2E: Kernel and Image of a Linear Transformation Exercises
- 7.03: Isomorphisms and Composition
- 7.3E: Isomorphisms and Composition Exercises
- 7.04: A Theorem about Differential Equations
- 7.05: More on Linear Recurrences
- 7.5E: Exercises for Linear Recurrences
- 08: Orthogonality
- 8.00: Prelude to Orthogonality
- 8.01: Orthogonal Complements and Projections
- 8.1E: Orthogonal Complements and Projections Exercises
- 8.02: Orthogonal Diagonalization
- 8.2E: Orthogonal Diagonalization Exercises
- 8.03: Positive Definite Matrices
- 8.3E: Positive Definite Matrices Exercises
- 8.04: QR-Factorization
- 8.4E: QR-Factorization Exercises
- 8.05: Computing Eigenvalues
- 8.5E: Computing Eigenvalues Exercises
- 8.06: The Singular Value Decomposition
- 8.6E: The Singular Value Decomposition Exercises
- 8.07: Complex Matrices
- 8.7E: Complex Matrices Exercises
- 8.08: An Application to Linear Codes over Finite Fields
- 8.8E: An Application to Linear Codes over Finite Fields Exercises
- 8.09: An Application to Quadratic Forms
- 8.9E: An Application to Quadratic Forms Exercises
- 8.10: An Application to Constrained Optimization
- 8.11: An Application to Statistical Principal Component Analysis
- 09: Change of Basis
- 9.00: Prelude to Change of Basis
- 9.01: The Matrix of a Linear Transformation
- 9.1E: The Matrix of a Linear Transformation Exercises
- 9.02: Operators and Similarity
- 9.2E: Operators and Similarity Exercises
- 9.03: Invariant Subspaces and Direct Sums
- 9.3E: Invariant Subspaces and Direct Sums Exercises
- 10: Inner Product Spaces
- 10.00: Prelude to Inner Product Spaces
- 10.01: Inner Products and Norms
- 10.1E: Inner Products and Norms Exercises
- 10.02: Orthogonal Sets of Vectors
- 10.2E: Orthogonal Sets of Vectors Exercises
- 10.03: Orthogonal Diagonalization
- 10.3E: Orthogonal Diagonalization Exercises
- 10.04: Isometries
- 10.4E: Isometries Exercises
- 10.05: An Application to Fourier Approximation
- 10.5E: An Application to Fourier Approximation Exercises
- 11: Canonical Forms
- 11.00: Prelude to Canonical Forms
- 11.01: Block Triangular Form
- 11.1E: Block Triangular Form Exercises
- 11.02: The Jordan Canonical Form
- 11.2E: The Jordan Canonical Form Exercises
- 12: Appendices
- 12.A: Complex Numbers
- 12.A: Complex Numbers
- 12.B: Proofs
- 12.B: Proofs
- 12.C: Mathematical Induction
- 1.00: Exercises for Mathematical Induction
- 12.D: Polynomials