Starting in Fall 2025 there will be some changes to EE263. In previous years the course was titled Introduction to Linear Dynamical Systems. It covered both an application-oriented approach to linear algebra, and an introduction to linear dynamical systems. Starting in Fall 2025 this course has now been split into two courses, the first will be EE263: Matrix Methods: Singular Value Decomposition, and cover an expanded version of the linear algebra from the old EE263. The emphasis is still very much on applications, and how to use the material, and how to formulate an enormous range of practical problems which can be addressed using these tools. The second course will be EE363: Linear Dynamical Systems, and will present more in-depth coverage of the second half of the old EE263. The new version of EE263 will provide good background for both EE363 and EE364a.
If you have taken the old EE263, you cannot (and should not) take this new version too. But you may wish to take EE363 in Spring.
Stanford's course information sites are not yet populated with the correct course description for EE263; the description below is up-to-date.
Looking forward to seeing you in Fall Quarter!
Mondays and Wednesdays, 9:30am - 10:50am
First lecture 9/22, last lecture 12/5
Location: Bishop Auditorium
This class will be taught live. All lectures will also be recorded (by SCPD/CGOE) and the videos will be posted on Canvas approximately one hour after the class ends.
Least-squares approximations of over-determined equations, and least-norm solutions of underdetermined equations. Range and nullspace and their connection to left and right inverses. Symmetric matrices and quadratic forms. Positive definite matrices. Newton's method. Vector Gaussian distributions. Eigenvalues and eigenvectors of symmetric matrices. Matrix norm and the singular-value decomposition. Spectral graph embedding. Low rank approximations. Emphasis on applications from a broad range of disciplines including circuits, signal processing, machine learning, and control systems.
Prerequisites: Linear algebra as in Engr108 or Math 104
A good reference for an introductory treatment of some parts of the course is the book Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares by Stephen Boyd and Lieven Vandenberghe. This is the textbook for engr108, and is available online.
The book is not required, and EE263 differs from the book. EE263 is at a more advanced level, and it covers much material that is not in the book. Complete notes for this class will be available online. See the section on reading for other references.
This course was originally developed and taught by Professor Stephen Boyd. The material from this version of the course, and the complete set of materials consisting of lecture videos, slides, support notes and homework is still available in the archive. This version substantially differs from the current version.