EE263: Introduction to Linear Dynamical Systems

Reza Nasiri Mahalati, Stanford University, Fall Quarter 2016

Instructor

Reza Nasiri Mahalati

Lectures

  • Tuesdays and Thursdays, 9:00am–10:20am in Gates B1

  • 20 lectures, starting Tuesday September 27, 2016.

Review sessions

  • Weekly review sessions will be held on Fridays 4:30pm–5:20pm in the Nvidia Auditorium, starting September 30.

  • Review sessions will be videotaped by SCPD and uploaded on their website the following week.

Exams

  • The midterm exam will be a 24hr take-home. Students can choose to take the midterm on 10/29 or 10/30 at 10:00-10:30am or 5:00-5:30pm and return it 24 hours later. So there are 4 total time/date options for taking the midterm.

  • The final exam will be a 24hr take-home. Students can choose to take the final on 12/10 or 12/11 at 10:00-10:30am or 5:00-5:30pm and return it 24 hours later. So there are 4 total time/date options for taking the final.

Course description

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, differential equations and Laplace transforms as in EE102A.

Textbooks

There are no required or optional textbooks. Complete notes will be available online. See the section on reading for details.

Announcements

We are using Piazza. We'll post most announcements there, not here, so make sure you join.

Archive

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.