Lecture

Data Compression and Shannon's Theorem: Performance Analysis

In course

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Description

This lecture explains Shannon's theorem, stating that the compression of a source cannot go below its entropy. It also discusses the performance of Shannon Fano codes, showing they are close to the theoretical optimum. The relationship between entropy and the average number of questions in a Shannon Fano code is explored, providing insights into the exact definition of entropy.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_fmwwpwy6

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Ontological neighbourhood

Information engineering

Signal processing: Data compression

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