© РИА Томск. Павел Стефанский
TOMSK, Dec 4 – RIA Tomsk. Mathematicians of Tomsk State University (TSU) developed methods that 10 times improve the
accuracy of evaluating information and allow to restore the image or
signal in complex telecommunication systems with high quality, the
university’s press service said on Wednesday.
"TSU mathematicians completed a project of the Russian Science
Foundation to develop mathematical methods for analyzing signals and
images in complex telecommunication and navigation systems that are
affected by random noise. The methods they created improve the accuracy
of information estimation up to 10 times and make it possible to restore
an image or signal with high quality", – is said in the message.
It is noted that the project is focused on the tasks of statistical
radiophysics – the problem of data transmission over communication
channels. The project executor – are scientists from the TSU
International Laboratory of Statistics of Stochastic Processes and
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"For example, an airplane flies, transmits a signal. During the
transmission of a signal, various noises are superimposed on it and,
accordingly, the receiver needs to obtain data that is as close as
possible to what was transmitted. Optimal algorithms are built that
allow to filter out noise phenomena and get a signal that is as close as
possible to the one actually transmitted", – the press service quoted
the head of the laboratory Evgeny Pchelintsev.
It is specified that the algorithms created at TSU take into account
qualitatively more complex noise in models than previously existed. The
results obtained by mathematicians will be used to build new radar
systems for operational analysis and monitoring of the environment,
satellite navigation systems, promising systems for information
receiving and transmitting.
It is added that now scientists of the TSU Faculty of Mechanics and
Mathematics have already received two patents for their inventions, a
prototype of a device for receiving information using their algorithm
was created at Moscow Power Engineering Institute (MPEI). Next year
scientists plan to apply their algorithms to the analysis of big data:
it can be the data of sociological surveys, physical or financial data.