Introduction to Linear Algebra
Systems of Linear Equations
- Introduction
- Linear Systems
- Vectors
- Linear combinations
- Matrices
- Planes in ℝ³
- Row operations
- Gaussian elimination
- Reduced Row-Echelon Form
- Equation A x = b
- Sensitivity of solutions
- Iterative methods
- Linear independence
- Plane transformations
- Space transformations
- Rotations
- Linear transformations
- Affine mapss
- Exercises
- Answers
Matrix Algebra
- Introduction
- Manipulation of matrices
- Matrix transformations
- Block matrices
- Determinants
- Cofactors
- Cramer's rule
- Partitioned matrices
- Elementary matrices
- Inverse matrices
- Equivalent matrices
- Elimination: A = LU
- PLU factorization
- Reflection
- Givens rotation
- Special matrices
- Exercises
- Answers
Vector Spaces
- Introduction
- Motivation
- Vector Spaces
- Bases
- Dimension
- Coordinate systems
- Change of basis
- Linear transformations
- Compositions
- Isomorphisms
- Dual spaces
- Dual transformations
- Subspaces
- Intersections
- Direct sums
- Quotient spaces
- Vector products
- Cross products
- Matrix spaces
- Row space
- Range or Column space
- Rank
- Null spaces or Kernels
- Dimension Theorems
- Four subspaces
- Solving A x = b
- Exercises
- Answers
Eigenvalues, Eigenvectors
- Introduction
- Characteristic Polynomials
- Algebraic and Geometric Multiplicities
- Minimal Polynomials
- Eigenspaces
- Where are Eigenvalues?
- Eigenvalues of AB and BA
- Generalized Eigenvectors
Euclidean Spaces
- Introduction
- Dot product
- Bilinear transformations
- Inner product
- Norm and distance
- Matrix norms
- Dual norms
- Dual transformations
- Orthogonality
- Gram--Schmidt Process
- Orthogonal sets
- Self-adjoint matrices
- Unitary matrices
- Projection operators
- QR-decomposition
- Least Square Approximation
- Quadratic forms
- Exercises
- Answers
Matrix Decompositions
- Introduction
- LU-decomposition
- Sylvester Formula
- Cholesky decomposition
- Schur decomposition
- Jordan decomposition
- Positive Matrices
- Roots
- Polar Factorization
- Spectral Decomposition
- Singular values
- SVD
- Pseudoinverse
- Exercises
- Answers
Applications
- GPS Problem
- Graph Theory
- Error Correcting Codes
- Electric Circuits
- Markov chains
- Cryptography
- Wave-length transfer matrix
- Computer graphics
- Linear Programming
- Hill's determinant
- Fibonacci matrices
- Discrete dynamic systems
- Discrete Fourier transform
- Fast Fourier transform
- Curve fitting
Functions of Matrices
- Introduction
- Similar matrices
- Diagonalization
- Sylvester Formula
- The Resolvent method
- Polynomial Interpolation
- Positive Matrices
- Roots
- Pseudoinverse
- Exercises
- Answers
Miscellany
- Circles along curves
- TNB frames
- Tensors
- Tensors in ℝ³
- Tensors & Mechanics
- Differential forms
- Calculus
- Vector Representations
- Matrix Representations
- Change of Basis
- Orthonormal Diagonalization
- Generalized Inverse
Preliminaries
- Complex Number Operations
- Sets
- Polynomials
- Polynomials and Matrices
- Computer solves systems of Linear Equations
- Location of eigenvalues
- Power method
- Iterative method
Glossary
Reference
This Book is licensed under Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License
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In many applications, we come across difference equations; the simplest of them is a first order vwxtor recurrence
\[
{\bf x}_{k+1} = {\bf A}\, {\bf x}+k , \qquad k=0,1,2,\ldots .
\]
It is always assumed that the initial vector x₀ is given.
- Borisenko, A.I., Tarapov, I.E., Vector and Tensor Analysis with Applications, Translated by R. Silverman. Dover Publications. Available at: https://www.perlego.com/book/110945/vector-and-tensor-analysis-with-applications-pdf (Accessed: 14 October 2022).
- Lay, D.C., Lay, S.R., McDonald, J.J., Linear Algebra and its Applications, Pearson,