Introduction to Linear Algebra

Author(s)
Deborah C. Arangno
Edition
1
Pages
101
Book Type
Academic

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The methods of Linear Algebra are used in applications that involve systems of equations to formulate, solve, and understand the solutions.

Linear algebra is a fundamental tool in modern applications of mathematics, used to solve many real-world problems, (scheduling flights, ranking webpages in search engines, or modeling fluid dynamics, etc.)

This book covers the essential ideas and methods of Linear Algebra and acquaints the reader with how to use the techniques of matrices and vector spaces in solving problems.

This book can be used for an undergraduate course on the foundations of Linear Algebra, designed for students in the sciences and engineering. After completing such a course, you should understand fundamental topics of linear algebra including vectors, matrices, linear systems, vector spaces, eigenvalues and eigenvectors, and orthogonality.

Chapter 1……. LINEAR SYSTEMS
1.1 Systems of Linear Equations
1.2 Row Reduction & Gauss Jordan Elimination
1.3 Vector Equation
1.4 Matrix Equation
1.5 Matrix Multiplication by a Vector
1.6 Solutions to Linear Systems
1.7 Linear Independence
1.8 Linear Transformations
The Matrix of a Linear Transformation
Chapter 1 Exercises

Chapter 2……. MATRIX OPERATIONS
2.1 Transpose of a Matrix
2.2 Matrix Multiplication
2.3 Properties of Matrix Multiplication
2.4 Identity Matrix
2.5 Matrix Inverses
2.5.1 Inverses of 2x2 Matrices
2.5.2 Inverses of N X N Matrices
2.5.3 Applying Inverse Matrices to Solving Systems of Equations
2.5.4 Properties of Inverse Matrices
2.6 Characterizations of Invertible Matrices
Chapter 2 Exercises

Chapter 3……. VECTOR SPACES
3.1 Vector Spaces and Subspaces
3.2 Column and Null Spaces of a Matrix
3.3 Dimension and Bases
3.4 Coordinates
3.5 Change of Basis
3.6 Vector Coordinates and Bases – Exercises
Chapter 3 Exercises

Chapter 4……. DETERMINANTS
4.1 Introduction to Determinants
4.2 Properties of Determinants
4.3 Cramer’s Rule
4.4 Application of the Determinant

Chapter 5……. EIGENVALUES & DIAGONALIZATION
5.1 Eigenvalues
5.2 The Characteristic Equation
5.3 Diagonalization
5.4 Eigenvalues and Eigenvectors – Exercises
Chapter 5 Exercises

Chapter 6……. INNER PRODUCT SPACES and ORTHOGONALITY
6.1 The Inner Product
6.1.1 Properties of The Inner Product
6.1.2 Interpretation of The Inner Product
6.1.3 Projections
6.2 Orthogonal Complements – Vector Spaces
6.3 Orthogonal Bases
6.4 The Gram-Schmidt Process
6.5 QR Factorization
6.6 Spectral Decomposition of a Symmetric Matrix
6.7 Orthogonality – Exercises
Chapter 6 Exercises

Deborah C. Arangno

The methods of Linear Algebra are used in applications that involve systems of equations to formulate, solve, and understand the solutions.

Linear algebra is a fundamental tool in modern applications of mathematics, used to solve many real-world problems, (scheduling flights, ranking webpages in search engines, or modeling fluid dynamics, etc.)

This book covers the essential ideas and methods of Linear Algebra and acquaints the reader with how to use the techniques of matrices and vector spaces in solving problems.

This book can be used for an undergraduate course on the foundations of Linear Algebra, designed for students in the sciences and engineering. After completing such a course, you should understand fundamental topics of linear algebra including vectors, matrices, linear systems, vector spaces, eigenvalues and eigenvectors, and orthogonality.

Chapter 1……. LINEAR SYSTEMS
1.1 Systems of Linear Equations
1.2 Row Reduction & Gauss Jordan Elimination
1.3 Vector Equation
1.4 Matrix Equation
1.5 Matrix Multiplication by a Vector
1.6 Solutions to Linear Systems
1.7 Linear Independence
1.8 Linear Transformations
The Matrix of a Linear Transformation
Chapter 1 Exercises

Chapter 2……. MATRIX OPERATIONS
2.1 Transpose of a Matrix
2.2 Matrix Multiplication
2.3 Properties of Matrix Multiplication
2.4 Identity Matrix
2.5 Matrix Inverses
2.5.1 Inverses of 2x2 Matrices
2.5.2 Inverses of N X N Matrices
2.5.3 Applying Inverse Matrices to Solving Systems of Equations
2.5.4 Properties of Inverse Matrices
2.6 Characterizations of Invertible Matrices
Chapter 2 Exercises

Chapter 3……. VECTOR SPACES
3.1 Vector Spaces and Subspaces
3.2 Column and Null Spaces of a Matrix
3.3 Dimension and Bases
3.4 Coordinates
3.5 Change of Basis
3.6 Vector Coordinates and Bases – Exercises
Chapter 3 Exercises

Chapter 4……. DETERMINANTS
4.1 Introduction to Determinants
4.2 Properties of Determinants
4.3 Cramer’s Rule
4.4 Application of the Determinant

Chapter 5……. EIGENVALUES & DIAGONALIZATION
5.1 Eigenvalues
5.2 The Characteristic Equation
5.3 Diagonalization
5.4 Eigenvalues and Eigenvectors – Exercises
Chapter 5 Exercises

Chapter 6……. INNER PRODUCT SPACES and ORTHOGONALITY
6.1 The Inner Product
6.1.1 Properties of The Inner Product
6.1.2 Interpretation of The Inner Product
6.1.3 Projections
6.2 Orthogonal Complements – Vector Spaces
6.3 Orthogonal Bases
6.4 The Gram-Schmidt Process
6.5 QR Factorization
6.6 Spectral Decomposition of a Symmetric Matrix
6.7 Orthogonality – Exercises
Chapter 6 Exercises

Deborah C. Arangno

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