EE103: Applied Numerical Computing

UCLA Electrical Engineering Department

Dr. Brien Alkire

Office hours: Tuesday from 1000-1200, Eng IV room 67-124, and by appointment


The EE103 lecture notes and course reader for Spring 2005/06 are available here in pdf format. For all other course information, homework assignments, and solutions, please refer to the EEweb course website.

Lectures notes

  1. Introduction.
  2. Vectors and matrices.
  3. Sets of linear equations.
  4. The solution of a set of linear equations.
  5. Solving linear equations.
  6. The LU factorization.
  7. The Cholesky factorization.
  8. Linear least-squares problems.
  9. The solution of a least-squares problem.
  10. The QR factorization.
  11. Least-norm problems.
  12. Nonlinear equations with one variable.
  13. Newton's method for sets of nonlinear equations.
  14. Unconstrained minimization.
  15. Nonlinear least-squares.
  16. IEEE floating point numbers.
  17. Problem conditioning and stability of algorithms.
  18. Numerical software .
  19. Linear programming and convex optimization .


Course reader

  1. Vectors and matrices. Matlab files for exercises 1, 4, 9: ch1ex1.m, ch1ex4.m, ch1ex9.m.
  2. Sets of linear equations. Matlab files: ch2ex19.m, ch2ex36.m, mylu.m.
  3. Linear least-squares problems. Matlab files: ch3ex3.m, ch3ex4.m, ch3ex6.m, ch3ex7.m, ch3ex8.m.
  4. Least-norm problems.
  5. Nonlinear equations.
  6. Unconstrained minimization. Matlab files: ch6ex3.m, ch6ex5.m.
  7. Accuracy of numerical algorithms. Matlab file: chop.m.


Matlab and programming requirements

Many of the homework assignments will involve programming with Matlab or Octave. Matlab is available in the SEASnet Computer Labs. Here is a simple Matlab tutorial: html format, pdf

Acknowledgement

Thanks to Professor Lieven Vandenberghe for the use of his course materials.