EE133A - Applied Numerical Computing (Spring Quarter 2017)

The EE133A course reader and lectures slides for the Spring 2017 Quarter are made available on this website. For other course information and homework solutions please consult the CCLE course website.

Textbook

The textbook and additional notes are available in pdf.

  1. Introduction to Applied Linear Algebra. Vectors, Matrices, and Least Squares. This is a draft of a book by S. Boyd and L. Vandenberghe. Additional material closely related to 133A can be found on the website of the Stanford course Introduction to Matrix Methods.

  2. EE133A Lecture Notes. Additional notes on topics not covered in the textbook.

Lecture slides

  1. Introduction
    Vectors

  2. Norm, distance, angle

  3. Matrices

  4. Matrix inverses

  5. Orthogonal matrices

  6. QR factorization

  7. Linear equations

  8. Least squares

  9. Least squares data fitting

  10. Multi-objective least squares

  11. Constrained least squares

  12. Cholesky factorization

  13. Nonlinear least squares

  14. Nonlinear equations

  15. Problem condition

  16. Algorithm stability

  17. IEEE floating point numbers

Homework

Homework is due at 5:00PM on the due date. There is a submission box in the TA meeting room (67-112 Engineering 4). Late homework will not be accepted.

Exercise numbers with prefix 'T’ refer to exercises in the textbook Vectors, Matrices, and Least Squares. Exercise numbers with prefix 'A’ refer to the collection of additional exercises. MATLAB files for the additional exercises can be found in the data file directory.

Homework solutions are posted on the CCLE course website. Homework grades are posted on MyUCLA. The graded homework will be returned by the TAs in the discussions.