Matrices: Matrix norm. Spectral decomposition, Singular value decomposition, convergence and perturbation theorem, Matrix eigenvalue problem, Eigen-value by iteration, Q-R Factorization, Generalized inverse of matrices; Approximation of functions: General function spaces, Least square approximation, orthogonal polynomials, approximation with rational functions, Pade’s approximation; Differential equations: Nonlinear system of differential equations- method of successive approximations, Use of Pade’s approximation, Lyapunov and Riccati equations.
Boundary Value Problems: Method of undetermined coefficients, Difference scheme based on quadrature formulas, solution of tridiagonal system, moving boundary conditions, boundary conditions at infinity, Non-linear boundary value problems, convergence of difference schemes, linear eigenvalue problems; Partial Differential Equations: Parabolic, Elliptic and Hyperbolic differential equations.

Suggested Text:

  1. Gene H. Golub and James M. Ortega. Scientific Computing and Differential Equations, Academic Press NewYork.
  2. K. Jain. Numerical Solution of Differential Equations
  3. G. Ancona. Computational Methods for Applied Science and Engineering
  4. Kendall E. Atkinson. An Introduction to Numerical Analysis
  5. Evans, Lawrence C. Partial Differential Equations.