Vector space examples. Inner products, orthogonal sets including Legendre polynomials, trigonometric functions, wavelets. Projections, least squares, normal equations, Fourier approximations. Eigenvalue problems, diagonalization, defective matrices. Coupled difference and differential equations; applications such as predator-prey, business competition, coupled oscillators. Singular value decomposition, image approximations. Linear transformations, graphics. Antirequisite(s): Prerequisite(s): Applied Mathematics 1413 or Calculus 1301A/B or 1501A/B and a minimum mark of 60% in Mathematics 1600A/B or the former Linear Algebra 1600A/B, or Applied Mathematics 1411A/B. Corequisite(s): Pre-or Corequisite(s): Extra Information: 3 lecture hours, 0.5 course. back to top
