Overview

Code solving UT Numerical Anaylsis excersizes

Fall M 387C

The fall focused on numerical optimization, approximation, and linear algebra. It is an introduction to scientific computing, theory and application of numerical linear algebra, solution of nonlinear equations, and numerical approximation of functions.

1. HW1 - Conditioning numbers, norms, floating point numbers
2. HW2 - Givens rotations, Conjugate gradient methods
3. HW3 - Singular value decompositions, Newton iterations
4. HW4 - Numerical optimization
5. HW5 - Splines, numerical integration
6. HW6 - Wavelets, Nueral networks

Spring M 387D

The spring excersizes focus on ODEs and PDEs. It is an introduction to the theory and practice of commonly used numerical algorithms for the solution of ordinary differential equations, and elliptic, parabolic, and hyperbolic partial differential equations. Three lecture hours a week for one semester.

8. HW1 - Euler methods,Dahlquist stability
9. HW2 - Linear multi-step methods
10. HW3 - Finite element methods
11. HW4 - Finite element methods
12. HW5 - Partial differential equations
13. HW6 - Finite volume methods, Finite difference methods