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Linear algebra: the theory of vector spaces and linear transformations
Aaron Greicius
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Front Matter
Colophon
Acknowledgements
0
Foundations
0.1
Sets
0.1
Exercises
0.2
Functions
0.2
Exercises
0.3
Tuples and Cartesian products
0.4
Logic
Propositional logic
Predicate logic
Exercises
0.5
Proof techniques
Logical structure
Implication
Disjunction
Equivalence
Chains of implications/equivalences
Proof by contradiction
Equalities
Chain of equalities
Basic set properties
Set inclusion
Set equality
Basic function properties
Function equality
Injective, surjective, bijective
Mathematical induction
Proof by induction
Proof by strong induction
0.6
Complex numbers
Definition of
\(\C\)
Absolute value and complex conjugation
Exercises
0.7
Polynomials
Basic definitions
Degree of a polynomial
Factoring polynomials
Exercises
1
Systems of linear equations
1.1
Systems of linear equations
Systems of linear equations
Row operations
Exercises
1.2
Gaussian elimination
Row echelon matrices
Gaussian elimination
Model example
Exercises
1.3
Solving linear systems
Model example continued
General method for solving linear systems
Exercises
2
Matrices, their arithmetic, and their algebra
2.1
Matrix arithmetic
The basics
Addition, subtraction and scalar multiplication
Matrix multiplication
Alternative methods of multiplication
Transpose of a matrix
Exercises
2.2
Matrix algebra
2.2
Exercises
2.3
Invertible matrices
Invertible matrices
Powers of matrices, matrix polynomials
Exercises
2.4
The invertibility theorem
Elementary matrices
Interlude on matrix equations
The invertibility theorem
Invertibility algorithms
Some theoretical loose ends
Exercises
2.5
The determinant
Definition of the determinant
Expansion along rows and columns
Row operations and determinant
Exercises
3
Vector spaces and linear transformations
3.1
Real vector spaces
Definition of a vector space
Examples
General properties
Exercises
3.2
Linear transformations
Linear transformations
Matrix transformations
Rotations, reflections, and orthogonal projections
Additional examples
Composition of linear transformations and matrix multiplication
Exercises
3.3
Subspaces
Definition of subspace
Subspaces of
\(\R^n\)
Important subspaces of
\(M_{nn}\)
Important subspaces of
\(F(I,\R)\)
Exercises
3.4
Null space and image
Null space and image of a linear transformation
Injective and surjective linear transformations
Exercises
3.5
Span and linear independence
Span
Linear independence
Linear independence in function spaces
Exercises
3.6
Bases
Bases of vector spaces
Bases and linear transformations
Exercises
3.7
Dimension
Dimension of a vector space
Street smarts!
3.8
Rank-nullity theorem and fundamental spaces
The rank-nullity theorem
Fundamental spaces of matrices
Contracting and expanding to bases
Exercises
3.9
Isomorphisms
Isomorphisms
4
Eigenvectors and diagonalization
4.1
Coordinate vectors
Coordinate vectors
Coordinate vector transformation
Exercises
4.2
Matrix representations of linear transformations
Matrix representations of linear transformations
Matrix representations as models
Choice of basis
Exercises
4.3
Change of basis
Change of basis matrix
Change of basis for transformations
Similarity and the holy commutative tent of linear algebra
Exercises
4.4
Eigenvectors and eigenvalues
Eigenvectors
Finding eigenvalues and eigenvectors systematically
Properties of the characteristic polynomial
Exercises
4.5
Diagonalization
Diagonalizable transformations
Linear independence of eigenvectors
Diagonalizable matrices
Algebraic and geometric multiplicity
Exercises
5
Inner product spaces
5.1
Inner product spaces
Inner products
Norm and distance
Cauchy-Schwarz inequality, triangle inequalities, and angles between vectors
Choosing your inner product
Exercises
5.2
Orthogonal bases
Orthogonal vectors and sets
Orthogonal bases
Coordinate vectors and matrix representations
Exercises
5.3
Orthogonal projection
Orthogonal complement
Orthogonal Projection
Orthogonal projection in
\(\R^2\)
and
\(\R^3\)
Trigonometric polynomial approximation
Least-squares solution to linear systems
Exercises
5.4
The spectral theorem
Self-adjoint operators
The spectral theorem for self-adjoint operators
Exercises
Back Matter
A
Notation
B
Exercises
C
Definitions
D
Theory and procedures
E
Examples
F
Sage examples
G
Figures and video examples
H
Mantras and fiats
Index
Colophon
Colophon
©2020—2023 Aaron Greicius
Permission is granted to copy, distribute and/or modify this document under the terms of the Creative Commons Attribution-ShareAlike (CC BY-SA) 4.0 International License
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