Reza Nasiri Mahalati, Stanford University, Fall Quarter 2017

Reza Nasiri Mahalati

Office hours: Thursday 10:30AM - noon (after lecture) in Packard 104

06/26/2017 - 12/7/2017

Tuesdays and Thursdays, 9:00AM - 10:20AM in NVIDIA Auditorium

No lecture on 11/21 or 11/23 for Thanksgiving

Weekly review sessions will be held on Fridays (starting 9/29)

from 1:30PM to 2:20PM in NVIDIA Auditorium

These sessions will be videotaped by SCPD and uploaded on their website the following week. Notes from the review sessions will be posted under the notes tab of the website.

The midterm exam will be a

**12hr take-home**. Students can choose to take the midterm on**11/3, 11/4 or 11/5**at**10:00-10:30AM or 5:00-5:30PM**(Only 5:00-5:30pm on 11/3) and return it 12 hours later. So there are 5 total time/date options for taking the midterm.The final exam will be a

**15hr take-home**. Students can choose to take the final on**12/8, 12/9 or 12/10**at**10:00-10:30AM or 5:00-5:30PM**(Only 5:00-5:30pm on 11/3) and return it 15 hours later. So there are 5 total time/date options for taking the final.

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.

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

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

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.