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 Friday, 8 April, 5-6pm at Hewlett 103
Midterm on Friday, April 15 from 3:20pm to 5:20pm, at 200-305.
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