Supervisors: Eugene Asarin and Aldric Degorre.
A mixed signal contain discrete and real-valued data. Discrete data corresoponds to events, the real-valued - to time or other physical measurments (temperature, speed) for example
a, 1.234, 0.17, b 3.141 a 2.71828 a 0.0001 b.
We want to compress such data - exactly for discrete data and with some precision for continuous data. The aim of this internship is to develop novel compression methods based on our recent developments on entropy of timed languages.
After a study of the state-of-art in approximate compression of mixed data, some of the following theoretical questions will be addressed:
the experimental part of the work could be as follows:
The ideal candidate should know basics of timed automata/languages (e.g. course 2-8-2 of MPRI) and have good programming skills; also some knowledge in information theory and/or functional analysis, would be welcome (but not necessary).