EE 278: Introduction to Statistical Signal Processing

Stanford University, Autumn Quarter 2019-2020

Course Outline

The following topics will be covered in the course:

  • Review of basic probability and random variables

  • Mean square error estimation, detection, and linear estimation

  • Random vectors and processes

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

  • Stationary random processes

  • Autocorrelation and power spectral density

  • Convergence and limit theorems

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.


Time: Tuesdays and Thursdays, 12:00PM - 1:20PM
Location: Thornt 110

Review Sessions

There will be weekly review sessions in which we will discuss that week's lecture topics as well as apply them in solving relevant exercises.
Time: 4:30-5:30PM
Location: 200-303

Course Requirements

Homework: There will be weekly homework sets.

  • Out: Thursdays, after class

  • Due: Thursdays at 11:59 pm on Gradescope

Midterm: The midterm will be a 24 hour take-home exam.

  • Out: Tuesday, October 29, at 4PM

  • Due: Wednesday, October 30, by 4PM

Final: The final will be a 24 hour take-home exam.

  • Out: Thursday, December 5, at 6PM

  • Due: Friday, December 6, by 6PM

Course Grade Distribution: 20% homework, 30% midterm, 50% final

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.

Balaji Prabhakar
Office hours: Wednesdays, 10:00AM - 11:30AM
Location: Packard 269

Ahmad Ghalayini
Office hours:

  • Mondays, 3:30PM - 4:30PM

  • Thursdays, 10AM - 11AM

Location: Packard 107


A Piazza forum will be available for students to post questions. Students are encouraged to assist each other and post answers on Piazza.
Sign up here.