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Lecture notes · MATH241 · 11 sections

Linear Algebra

A complete set of lecture notes, typed up from the handwritten originals with every mistake fixed. They run from complex numbers through linear algebra to transforms and differential equations, with the same few ideas underneath.

The sections

Each section keeps every line of the original notes, in order, and can be read online or taken away as a PDF or as LaTeX.

1Complex NumbersReal and imaginary parts, complex arithmetic, conjugates and modulus, the triangle inequality, Euler's formula and the polar form.
  • Algebra of complex numbers
  • Conjugate and modulus
  • Triangle inequality
  • Euler's formula
Notes pages 1–7  ·  Read online, PDF, LaTeX
2Linear Systems, Matrices and Vector SpacesSolving linear systems by Gauss and Gauss–Jordan elimination, when solutions exist and when they are unique, and the first look at vector spaces, norms, dot products and the Cauchy–Schwarz inequality.
  • Gauss elimination
  • Gauss–Jordan and pivoting
  • Vector spaces
  • Norms and dot products
Notes pages 7–21  ·  Read online, PDF, LaTeX
3Span, Subspaces and BasesSpan, subspaces, linear independence, bases and dimension, then orthogonal bases, best approximation by projection and the Gram–Schmidt process.
  • Span and subspaces
  • Linear independence
  • Basis and dimension
  • Projection and Gram–Schmidt
Notes pages 22–31  ·  Read online, PDF, LaTeX
4Matrices, Determinants and Inverse MatricesMatrix algebra and partitioning, the transpose, determinants, row and column spaces and rank, the null space, inverses, Cramer's rule and LU factorization.
  • Matrix operations
  • Determinants
  • Rank and null space
  • Inverses and LU
Notes pages 32–52  ·  Read online, PDF, LaTeX
5Eigenvalues, Diagonalization and Symmetric MatricesEigenvalues and eigenvectors, why symmetric matrices are special, diagonalization, the Cayley–Hamilton theorem and functions of a matrix such as the matrix exponential.
  • Eigenpairs
  • Symmetric matrices
  • Diagonalization
  • Cayley–Hamilton and e^(At)
Notes pages 53–65  ·  Read online, PDF, LaTeX
6Singular Value DecompositionExtra notes. Where the singular values and singular vectors come from, how the decomposition scales space, and the rank-one expansion of a matrix.
  • Singular values
  • Singular vectors
  • Scaling picture
  • Rank-one expansion
Notes pages Extra notes  ·  Read online, PDF, LaTeX
7Quadratic FormsQuadratic forms and their canonical form, positive and negative definiteness, and least-squares curve fitting through the normal equations.
  • Canonical form
  • Definiteness
  • Curve fitting
  • Normal equations
Notes pages 65–68  ·  Read online, PDF, LaTeX
8Linear Constant Coefficient Difference EquationsDifference equations written as a matrix recursion and solved with eigenvectors, or with the roots of the characteristic equation, including repeated roots.
  • Matrix form
  • Eigenvector solution
  • Characteristic roots
  • Repeated roots
Notes pages 69–72  ·  Read online, PDF, LaTeX
9Z-Transform and Linear Differential EquationsThe z-transform and its properties for solving difference equations, then linear constant-coefficient differential equations, stability, and an RLC oscillator example.
  • Z-transform
  • Solving difference equations
  • Differential equations
  • Stability and oscillators
Notes pages 73–83  ·  Read online, PDF, LaTeX
10Laplace TransformDefinition and existence of the Laplace transform, its main properties, convolution, and solving linear differential equations with it.
  • Definition and existence
  • Properties
  • Convolution
  • Solving differential equations
Notes pages 84–89  ·  Read online, PDF, LaTeX
11Systems of Linear Differential EquationsSystems of differential equations solved by Laplace transform and by the state-transition matrix, variation of parameters, and extra notes on time-varying systems.
  • Systems and Laplace
  • State-transition matrix
  • Variation of parameters
  • Time-varying systems
Notes pages 89–96 + extra notes  ·  Read online, PDF, LaTeX

Notation

The handwritten notes mark the type of an object by underlining it. Here the usual textbook convention is used instead.

ObjectIn the handwritten notesOn these pages
Scalar (a number)plain, aitalic, a, α, c
Complex numberunderlined once, zitalic, z (it is a scalar)
Vectorunderlined once, ubold, u
Matrixunderlined twice, Aitalic capital, A (zero matrix O, identity I)

So the equation written Ax = c in the notes appears here as Ax = c.

Take it with you

The whole corrected set as one PDF. Every section also has its own PDF and a zip with the LaTeX source, so you can take out just the part you need.