EE 278: Course Information

Stanford University, Ahmad Ghalayini, Summer Quarter 2017-2018


You can find the course syllabus in pdf format here.

Course Outline

The following topics will be covered in the course:

  • Review of basic probability and random variables

  • Random vectors and processes

  • Convergence and limit theorems

  • IID, independent increment, Markov, and Gaussian random processes

  • Stationary random processes

  • Autocorrelation and power spectral density

  • Mean square error estimation, detection, and linear estimation.


There will be 15 lectures during this summer quarter, which extends from June 25 to August 16 2018.
Time: Mondays and Wednesdays 11:30 AM-1:20 PM
Venue: Huang 18
Lecture Videos: For this quarter, the lectures will be live streamed. The live streams will be available on canvas, under the page BETA- Lecture Videos. They will also be made available on the same page 20 minutes after the lecture ends. Another way to access the lecture videos is through SCPD's mvideox website. Lectures there will be posted 2 hours after each class.

Office hours

Office hours will be held each week. Office hours are intended to be a time for discussion about general class topics, homework, and review exercises.

Ahmad Ghalayini
Email: ghalayini AT stanford DOT edu
Office hours: Tuesdays 2-4PM
Packard 109


We will be using a class Piazza forum to conduct all discussions about course materials, answer questions about homework and review exercises, and post announcements outside of the scheduled lectures and office hours.
Please sign up here.

Course Requirements

Homework: There will be weekly homework sets. They will be made available on Tuesdays and are due on the following Tuesdays at 11:59 pm.

Midterm: There will be an evening midterm exam during week 5 of the quarter.

Final: There will be a final take-home exam during the last week of the quarter.

Grading guideline: 20% Homework, 35% Midterm, 45% Final

Course Prerequisites

EE 178 and linear systems and Fourier transforms at the level of EE 102A,B or EE 261, basic linear algebra, and basic knowledge of a language like MATLAB or Python to do some simulation exercises.