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The projects consists in
- Information Theory is a part of Probability Theory, initially developed
by Claude Shannon in 1948, as a tool for optimising the transmission
(coding - decoding) in a communication channel with limited capacity.
- Its key concept is entropy, measuring the uncertainty associated with
a probabilistic experiment - or equivalently the information gained
by an observation; other well-behaved indices derived from entropy also
permit to measure fundamental quantities such as the dependency between
two variables, the dissimilarity between two distributions, or the redundancy
of a categorical time series.
- Consequently, Information Theory has important applications beyond
Communication Engineering, namely in Complexity Theory, Life Sciences,
Physics, Linguistics and other human sciences.
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The course is intended for various audiences. Its first implementation,
though, is intended for the students of the University of Lausanne (cohort
2002-2003). Others visitors are welcome on the site, but only as guests.
In the future, students registered with the partner institutions will
be provided with personal accounts.
Access
to the course:
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