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.
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