###EE 636 – MATRIX COMPUTATIONS Year for which the review is written: 2013-14

Professor who took the course: Prof. Madhu Belur

Motivation behind the course:

Matrices are the heart of linear algebra.They are compact representations ,easy to manipulate.They are used by everybody – physicists, biologists, and mathematicians to organize information and study many complex phenomena.This course covers a lot of important tools with respect to linear algebra and matrices, which will be useful in a lot of circumstances (including placements). There will be couple of programming assignments and the load is appropriate for a 6 credit course.

Course Content:

Roughly the following topics will be covered:

-LU Decomposition, -Cholesky Decomposition, -Least Square Methods for linear equations, -Projection Matrices. -Iterative methods for generalized Eigenvalue problems., -Singular Value Decomposition -Perturbation bounds A more detailed version can be seen here.

Course Prerequisite: A little comfort with linear algebra will help, but generally do not require any strong pre-requisites

Feedback on Lectures:

80% Attendance was compulsory.

Everything covered in the lectures was from the prescribed textbooks. No slides were provided except for some one or two.

Feedback on assignments, tutorials and exams:

There were regular tutorial sessions in the class with TA’s present.If you solve the tutorial properly you don’t have to worry about the exam preparation.

There was a computing assignment based on Scilab.It was fairly easy and was weighted.

Exams were moderate and tested your concepts and computational abilities too.

Difficulty level: Moderate

Textbooks:

Van, Golub Matrix Computations

Softwares Used:

SCILAB

Reference books:

David Watkins Fundamentals of Matrix Computations

Contact details of reviewer: kunalphalakiit@gmail.com