EE278: Introduction to Statistical Signal Processing

David Tse, Stanford University, Autumn 2020

Overall Contents

Law of large numbers and central limit theorem; random vectors; hypothesis testing and classification; minimum mean square error estimation, Kalman and Wiener filtering; introduction to compressed sensing. Gaussian, Markov processes; stationarity; autocorrelation and power spectral density.

Lectures

Tue, Thu 2:30 - 3:50 pm, remotely. Watch the lectures live from the Zoom tab on Canvas.

Zoom Etiquette:

  • Do not record the Zoom meetings. It is against Stanford rules and applicable law.

  • Please keep your mic muted unless you are speaking, to minimize background noise.

  • Please keep your video on. We would like to make our online class experience as close to a regular in-person class as possible. You would not want to be invisible to the instructor and your classmates if you were attending a regular in-person class.

  • Feel free to use the Zoom chat. The TA and other students can answer questions during the lecture. The instructor may not be able to monitor the chat in real time.

  • Raise your hand (physically) to signal that you have a question. Should the instructor overlook your raised hand, unmute your mic, then say “question”.

  • An example of a viable Zoom user interface configuration can be found here.

Announcements