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• Содержание выпуска • • Methods for Optimal Control and Control Theory • • Mathematical Foundations of Programming • • Healthcare Information Systems • • Artificial Intelligence, Intelligence Systems, Neural Networks • • Software and Hardware for Distributed Systems and Supercomputers •
Mathematical Foundations of Programming
Responsible for the Section: doctor of physico-mathematical Sciences
Nikolay Nepeivoda
On the left: assigned number of the paper, submission date, the number
of A5 pages contained in the paper, and the reference to the full-text
PDF
.
Article #
18_2019
51
p.
PDF |
submitted on 26th Jule 2019 displayed on
website on 28th
Nov
2019
Vitaly
Fralenko, Yulia Emelyanova, Oleg Shishkin, Anton Liseytsev
Intellectual support of processes of control and diagnostics of
space subsystems
We study the subject area is carried out, a review of existing
developments in the field of constructing monitoring systems,
monitoring and diagnostics of subsystems of spacecraft, including
using the neural network approach. Theoretical studies was aimed at
the implementation of mathematical and algorithmic support for the
monitoring and diagnostics system of spacecraft subsystems. Our
search for solutions was resulted in methodological approaches and
methods for solving technical problems on the construction of a
neural network monitoring system and diagnostics of subsystems of
the spacecraft. The use of artificial neural network technologies
makes it possible to detect, classify and predict errors, carry out
multilevel diagnostics of subsystems of the spacecraft and predict
their further behavior, thereby increasing the efficiency, speed of
decision making and the reliability of the nodes of the spacecraft.
The presented method of graphical representation of time sequences
allows visual classification of the radio signal and noise
detection. We propose to form and rank a set of significant features
by applying the Add and Del algorithms. (In Russian).
Key words: spacecraft, monitoring, diagnostics, forecasting,
artificial neural networks, intellectual support, cognitive
visualization, cognitive representation of the radio signal.
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article citation |
http://psta.psiras.ru/read/psta2019_4_25-75.pdf |
DOI |
https://doi.org/10.25209/2079-3316-2019-10-4-25-75 |
Article #
19_2018
20
p.
PDF |
submitted on 28th Feb 2019 displayed on
website on 30th
Nov
2019
Alexey
Rybakov, Sergei Shumilin
Study of the vectorization efficiency of loop nests with an
irregular number of iterations
Computation vectorization is an important low-level optimization
used to create highly efficient parallel code. However, when used in
context with an unknown program execution profile, a danger of low
effectiveness of the application emerges. This is especially
pronounced when vectorizing nests of cycles with an irregular number
of iterations of the inner loop. The article discusses a comparison
of the theoretical and practical efficiency of vectorization on the
example of Shell sorting, since this program code is extremely
inconvenient for vectorization.
(In Russian).
Key words: vectorization, AVX-512, loop sockets with an
irregular number of iterations, Shell sorting, theoretical
acceleration.
|
article citation |
http://psta.psiras.ru/read/psta2019_4_77-96.pdf |
DOI |
https://doi.org/10.25209/2079-3316-2019-10-4-77-96 |
• Содержание выпуска • • Methods for Optimal Control and Control Theory • • Mathematical Foundations of Programming • • Healthcare Information Systems • • Artificial Intelligence, Intelligence Systems, Neural Networks • • Software and Hardware for Distributed Systems and Supercomputers •
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