EE263 Introduction to Linear Dynamical Systems

Autumn Quarter 2014


  • Tuesdays and Thursdays, 9:30–10:45am in Nvidia Auditorium.

  • The first lecture is on Sep 23, the last is on Dec 4.

Review sessions

  • Fridays, 9:00–9:50am in Nvidia Auditorium.

  • The first session is on Oct 3.

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.


Professor Sanjay Lall and teaching assistants Aditya Timmaraju, Reza Takapoui, Bobbie Chern, Philip Lee, and Jiafan Yu.


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

Reference material

There are no required or optional textbooks. Everything we will use will be posted on the course website. However, several texts can serve as auxiliary or reference texts.

  • Linear Algebra and Its Applications, G. Strang

  • Matrix Analysis and Applied Linear Algebra, C.D. Meyer

  • Introduction to Dynamic Systems, D. Luenberger

  • Computational Science and Engineering, G. Strang

  • Linear Algebra Done Right, S. Axler

You will not need these books, and none of them cover exactly the material that we will be covering. We only list them in case you want to consult some additional references.

Course requirements and grading

  • Weekly homework assignments are due at 5pm, usually on Fridays. Late homework will not be accepted. You are allowed to work on the homework in small groups, but must write up your own homework to turn in. Unless you are an off-campus student registered with SCPD, you must turn in a paper copy of your homework; you cannot submit electronically for this class.

  • Homework will be graded roughly, on a coarse scale of 1-10.

  • Homework assignments will typically make extensive use of Matlab. You can use it on Stanford shared computing machines or purchase the student edition for $75 from Stanford software licensing. Matlab is also available on the machines in the Terman engineering library.

  • The midterm exam will be a 24hr take-home, available for pickup on 10/24 or 10/25.

  • The final exam will be a 24hr take-home, available for pickup between 12/5 and 12/9.

  • Homework 15%, midterm 40%, final 45%. These weights are approximate; we reserve the right to change them later.