Becoming familiar with the theoremes of the information theory and reachable limits of communication.

Students acquire the information theory elements and are able to apply them in the design of communication systems and devices.

Source coding (statistical coding), AER lemma, Kraft-McMillan lemma, Shannon’s first theorem, damaged data source compression; Protection coding (information channel capacity and calculation methods, cascaded channels, optimal docoding). Performance criteria, channel code capacity, features of a binary symetrical channel, Shannon’s second theorem, typical sequence access; Cryptographic coding (the unique point, basic cryptographic algorithms), geometrical approach to the design and analysis of transmitters and receivers (vector channels, multivector channels, decision making, wave channels, Gram-Schmidt’s process, signal synthesis, geometrical interpretation, corelational receiver, adaptive filter, irrelevant data in adaptive filtering, error probability, error bounds on the error probablitiy, the transmission speed, signal energy per bit of information, the impact of bandwidth. The limiting relationship between signal and noise (-1.6 dB); multi-user information theory.

Lectures. Practice. Powerpoint.