EE 178 – Probabilistic Systems Analysis

Andrea Montanari, Stanford University, Spring 2016

Probability is the basic tool for modeling and analyzing systems in which uncertainty, noise, randomness play important roles. Its engineering applications include: networking (to model the traffic patterns), communications and signal processing (to model the channel or sensing noise), machine learning and artificial intelligence (to model uncertainty in reasoning), randomized algorithms, and so on.

This class provides an introduction to the basc concepts of probability: Probability spaces, independence, expectation and conditional expectations, large system asymptotics, and simple stochastic processes.

Class Times and Locations

  • Tue-Thu 1:30PM-2:50PM, Building 540, Room 108


Review session on Tuesday, May 31, 5-6 pm, at 200-305.

In-class final exam on Friday, June 3, 3:30pm-6:30pm, at 540-108.