Sanjay Lall, Stanford University, Fall Quarter 2023

Mondays and Wednesdays, 3:00pm - 4:20pm

First lecture 9/27, last lecture 12/06

Location: Skilling Auditorium

This class will be taught live. All lectures will also be recorded (by SCPD) and the videos will be posted on Canvas approximately one hour after the class ends. The lectures will also be viewable live remotely on Canvas.

Applied linear algebra and linear dynamical systems with applications to circuits, signal processing, communications, and control systems. Topics: least-squares approximations of over-determined equations, and least-norm solutions of underdetermined equations. Symmetric matrices, matrix norm, and singular-value decomposition. Eigenvalues, left and right eigenvectors, with dynamical interpretation. Matrix exponential, stability, and asymptotic behavior. Multi-input/multi-output systems, impulse and step matrices; convolution and transfer-matrix descriptions. Control, reachability, and state transfer; observability and least-squares state estimation.

Prerequisites: linear algebra and matrices as in MATH104 or Engr108; differential equations as in EE102A.

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, and the complete set of materials consisting of lecture videos, slides, support notes and homework is still available in the archive.