# 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.

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.

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

## Lecture slides

Introduction

Vectors

Norm, distance, angle

Matrices

Matrix inverses

Orthogonal matrices

QR factorization

Linear equations

Least squares

Least squares data fitting

Multi-objective least squares

Constrained least squares

Cholesky factorization

Nonlinear least squares

Nonlinear equations

Problem condition

Algorithm stability

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.