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.


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.

  3. Additional exercises. MATLAB files for the additional exercises can be found in the data file directory.

Lecture slides

  1. Introduction

  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