ISSN 1991-2927
 

ACP № 3 (65) 2021

Keyword: "cluster"

Nikita Aleksandrovich Pchelin, Candidate of Sciences in Engineering; graduated from the Ulyanovsk Higher Military Command School of Communications; completed his postgraduate studies at Ulyanovsk State Technical University; Chief Designer at Federal Research and Production Center Joint-Stock Company ‘Research-and- Production Association ‘Mars’; an author of articles and RF patents in the field of error-correcting coding. e-mail: pna3@yandex.ruN.A. Pchelin

Mohammed A. Y. Damdam, Postgraduate Student of the Department of Telecommunications of Ulyanovsk State Technical University majoring in Informatics and Computer Engineering; graduated from UlSTU; an author of publications in the field of error-correcting coding and information protection. e-mail: dam_love@mail.ruM.A.Y. Damdam

Ali S.A. Al-Mesri, Postgraduate Student of the Department of Telecommunications of Ulyanovsk State Technical University majoring in Informatics and Computer Engineering; graduated from UlSTU; an author of publications in the field of error-correcting coding and information protection. e-mail: ali_almassry@mail.ruA.S.A. Al-Mesri

Aleksandr Aleksandrovich Brynza, Master’s Student at the Department of Telecommunications of Ulyanovsk State Technical University majoring in Infocommunication Technologies and Communication Systems; an author of publications in the field of error-correcting coding and information protection. e-mail: abrynza73@gmail.comA.A. Brynza

The paradigm of neural network decoding of non-binary redundant codes63_8.pdf

The use of noise-tolerant coding in modern communication systems remains the only means of increasing the efficient energy of such systems. This parameter tends to increase in conditions when the receiver of the communication system is able to correct errors of a large multiplicity. At the same time, the existing experience of using various methods for decoding the received data to achieve such a goal in the format of algebraic or iterative procedures does not give a noticeable effect and leads to a large time cost and an exponential increase in the complexity of implementing the decoder processor. The reason for this situation is the passive position of the receiver, which, when processing each code vector, remains a fixator of the picture that occurred in the communication channel and, in general, by compiling a system of linear equations and then solving it, tries to identify the error vector. Some exceptions are permutation decoding systems, which, by selecting and using reliable characters from the number received at the reception, simulate the operation of their transmitter and compare the received (almost error-free) result of such encoding with the received combination [1, 2]. With the growing influence of destructive factors, such methods are ineffective. A natural question arises: are modern solutions in neural network technologies capable of improving the characteristics of code vector recognition systems in order to obtain acceptable machine time costs in order to achieve an increase in the energy characteristics of communication systems.

Neural networks, redundant codes, cluster, pattern recognition.

2021_ 1

Sections: Mathematical modeling

Subjects: Mathematical modeling.



Anatolii Afanasevich Gladkikh, Doctor of Sciences in Engineering; graduated from the Marshal Budjonny Military Academy of Signal Corps; completed his postgraduate studies at the same Academy, Professor of the Telecommunication Department at Ulyanovsk State Technical University; an author of monographs, textbooks, papers, and patents in the field of noise-immune coding and information security. e-mail: a.gladkikh@ulstu.ruA.A. Gladkikh,

Anastasiia Denisovna Bakurova, Master Student of the Telecommunication Department at Ulyanovsk State Technical University majoring in Infocommunication Technologies and Communication Systems; an author of publications in the field of noise-immune coding and information security. e-mail: bakurova.ad@mail.ruA.D. Bakurova,

Artem Vladimirovich Menovshchikov, Postgraduate Student of the Telecommunication Department at Ulyanovsk State Technical University; graduated from the Military Academy of Communications (Affiliated Branch of Novocherkassk) with a degree in the Communication Networks and Switching Systems; an author of publications in the field of noise-immune coding and information security. e-mail: menovshikov@ulstu.ruA.V. Menovshchikov,

Basem A.S. Said, Postgraduate Student of the Telecommunication Department at Ulyanovsk State Technical University; graduated from Ulyanovsk State Technical University with the Master’s Degree in Telecommunication Technologies and Communication Systems; an author of publications in the field of noise-immune coding and information security. e-mail: alsamery@mail.ruBasem A.S. Said,

Sergei Valentinovich Shakhtanov, graduated from the Leningrad Higher Military Engineering School of Communications; Senior Lecturer of the Department of Infocommunication Technologies and Communication Systems at the Nizhny Novgorod State University of Engineering and Economics; an author of publications in the field of noise-immune coding and information security. e-mail: r155p@bk.ruS.V. Shakhtanov

Fractal clustering of group codes in the system of galois field62_9.pdf

The permutation decoding (PD) of group systematic noise-immune codes is proved to be the most efficient method in using the redundant data entered to the code as against other methods of decoding digital data [1-5]. This opens up the opportunity of solving a complex computational problem of finding an equivalent code (EC), which is used to search for the error vector. The essence of this solution is that the computational procedure of real-time search for EC for each new combination of redundant code is replaced by a preliminary process of training the decoder to put in accordance with each new permutation of characters the generating matrix of EC parameters, which are recorded in the decoder’s memory card during training. Thus, such a memory card is called a cognitive card (CC). The article estimates the memory size of the CC, when using the block code (15,7,5), and shows the possibility of implementing a permutation decoder on basis of existing integrated circuits based on proven statements. For the first time, the apparatus of fractal partitioning of augmented binary Galois fields using the clustering of the common space of code vectors of a given code is used to prove the main statements. An efficient algorithm is presented to search for a set of invertible matrices of rearranged codes that do not provide an EC and for this reason should be primarily detected in the decoding procedure of the received code vectors.

Permutation decoding, cognitive decoder map, fractal, cluster.

2020_ 4

Sections: Mathematical modeling

Subjects: Mathematical modeling.



Valeriia Vadimovna Voronina, Ulyanovsk State Technical University, Candidate of Engineering; graduated from the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University; Associate Professor at the Department of Information Systems of Ulyanovsk State Technical University; an author of articles in the field of intellectual analysis of time series. [e-mail: vvsh85@mail.ru]V. Voronina,

Sergei Orestovich Smerechinskii, “AIS Gorod” Company, Magister; finished his Master’s studies at the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University; Software Engineer at “AIS Gorod” Company; an author of articles in the field of software development. [e-mail: quigon173@gmail.com]S. Smerechinskii

The System for Modelling the Cluster Simulating Processes of Big Data Analysis 000_9.pdf

The subject area for processing Big Data with the use of cluster systems is described in the article. The paper examines the existing methods of processing Big Data on which the proposed solution for increasing the efficiency of the cluster functioning is based. As basic solutions for building and proposing ways to increase the efficiency of the cluster, the Hadoop technology and the MapReduce methodology were chosen. The efficiency of cluster systems involves consideration of cluster processes in the form of the hierarchical architecture consisting of three levels: cluster node level, cluster segment level and cluster topology level. The paper indicates solutions that can be useful in order to improve the efficiency of cluster resource allocation by choosing the topology of cluster construction, using the more efficient load-balancing algorithm, and using graphics processors, which involves distributing computational loads between CPU and GPU. Recommendations proposed in the article are verified experimentally.

Big data, cpu, gpu, mapreduce, big data, cluster, balancing algorithm, topology, cpu, gpu, mapreduce.

2017_ 3

Sections: Information systems

Subjects: Information systems, Automated control systems.


Pavel Vladimirovich Dudarin, Ulyanovsk State Technical University, Postgraduate Student at the Department of Information Systems of Ulyanovsk State Technical University (UlSTU); graduated from the Ulyanovsk State Technical University; an author of papers in the field of text clustering. [e-mail: PDudarin@ibs.ru]P. Dudarin,

Aleksandr Petrovich Pinkov, Ulyanovsk State Technical University, Candidate of Economics, graduated from Ulyanovsk branch of Kuibyshev Planning Institute; Acting Rector of Ulyanovsk State Technical University, an author of more than 50 papers, a monograph, and articles in the field of economics, planning, marketing, production engineering, higher education organization, and corporate training. [e-mail: rector@ulstu.ru]A. Pinkov,

Nadezhda Glebovna Yarushkina, Ulyanovsk State Technical University, Doctor of Engineering, Professor; First Vice-Rector - Vice-Rector for Scientific Affairs of Ulyanovsk State Technical University; Head of the Department of Information Systems of UlSTU; graduated from Ulyanovsk Polytechnic Institute; an author of more than 300 papers in the field of soft computing, fuzzy logic, and hybrid systems. [e-mail: jng@ulstu.ru]N. Yarushkina

Methodology and the Algorithm for Clustering Economic Analytics Object 000_12.pdf

The purpose of the study, the results of which are described in the article, consist in developing new and modified methods and algorithms for solving the problem of clustering objects of economic analytics. The use of known algorithms for clustering formulations of economic indicators in order to determine the similarity of objects is complicated by the fact that the formulation of indicators are very short and the traditional indicators of terms occurrence (frequency) are inadequate. In addition, widespread occurrence of interviews and various forms of questionnaires in economic analysis implies the use of linguistic estimates. For example, "customer satisfaction level" indicator is difficult to quantify, so, instead of conventional points, fuzzy values such as “high”, “medium”, “low” are often used. As a result, it becomes feasible to use a fuzzy variant of the k-means method - the method of fuzzy k-means. Typically, the number of indicators in economic analysis is quite big, which makes it advisable to modify the algorithm on the basis of parallel execution. The study addresses the following issues: the k-means method is modified, it is adapted to the characteristics of the economic analytics objects; the methodology of data preprocessing for clustering is developed; new versions of clustering objects of economic analytics are developed, and experimental research of the effectiveness of the developed methods for large volumes of data is carried out.

Fcm-алгоритм, clustering, method of k-means, economic analysis, big data, fcm-algorithm, parallelization.

2017_ 1

Sections: Artificial intelligence

Subjects: Artificial intelligence.


Anna Aleksandrovna Shagarova, Marshal Bugaev Ulyanovsk Civil Aviation Institute, Senior Lecturer at the Department of All-professional Disciplines of Marshal Bugaev Ulyanovsk Civil Aviation Institute; an author of publications in the field of diversity reception of signals in the wireless networks of information transfer. [e-mail: Nutka82@list.ru]A. Shagarova

Methods for Improving the Efficiency of Decameter Range Aviation Digital Radio 000_7.pdf

In aviation telecommunication, decameter range is widely used for solving different tasks associated with the objective functions of aircrafts during their interaction among themselves and with ground means. Considering the features of the specified wavelength range due to the wide development of digital data exchange methods, the challenge of achieving their credibility is arised. The solution can be found only in the way of conjunctive use of data protection tools.In the paper, the author describes the application of hierarchical modulation for transmission of error correcting code combinations processed with clustering on the receiver. It allows implementing the list decoding of received code vector with the use of the only one list, and, consequently, it simplifies the decoder. The method is effective only with correct recovery of cluster number. The cluster number bits are transmitted in hierarchical modulation with the use of the point of signal constellation remoted from each other in the most greatly manner. Also, the author estimates probabilistic system characteristics.

Signal-to-code design, hierarchical modulation, cluster, list decoding.

2016_ 2

Sections: Mathematical modeling

Subjects: Mathematical modeling, Automated control systems, Architecture of ship's system.


Georgii Mikhailovich Tamrazian, Ulyanovsk State Technical University, ost-Graduate Student at the Department of Telecommunications of Ulyanovsk State Technical University; graduated from Ulyanovsk State Technical University; an author of articles and patents in the field of redundant code soft decoding. [e-mail: tamrazz@bk.ru]G. Tamrazian,

Anatolii Afanasievich Gladkikh, Ulyanovsk State Technical University, Candidate of Engineering; graduated from S.M. Budyonny Military Communications Academy; finished his post-graduate studies at the same academy; Professor at the Department of Telecommunications at Ulyanovsk State Technical University; an author of a monograph, textbooks, articles, and patents in the field of noiseless coding and information security. [e-mail: a.gladkikh@ulstu.ru]A. Gladkikh,

Dmitrii Vladimirovich Ganin, Nizhny Novgorod State University of Engineering and Economics, Candidate of Economics, Associate Professor; graduated from Nizhny Novgorod State Agricultural Academy; Head of the Department of Infocommunication Technologies and Telecommunications at Nizhny Novgorod State University of Engineering and Economics; an author of articles in the field of infocommunications. [e-mail: ngiei135@mail.ru]D. Ganin

Hardware Implementation of the Optimal Ldpc Decoder 000_14.pdf

Low Density Parity Check (LDPC) codes become more useful in modern infocommunication systems because of their error-correcting capability. At the present time, LDPC codes have reached Shannon’s limit. Moreover, the application of such codes unlike the turbo codes don’t have any license limitations. These factors have become the cause of growing interest to LDPC codes. Despite an easy way of the codec implementation, soft decoding of LDPC codes is a complex computational process. This article deals in more detail with the main problems concerning the hardware implementation of LDPC decoder and the ways of their solving. It also demonstrates the simulation results of different ways to decoder implementation and the comparison of these ways. Furthermore, the article presents the method of LDPC codes list decoding that reduces materially computational load on decoder and speeds up its work operation. The use of various procedures and mechanisms described in the article will help to generate the optimal LDPC code decoder designed for a certain task.

Ldpc-код, ldpc code, soft decoder, fpga, cluster, tanner graph, list decoding.

2015_ 3

Sections: Electronic and electrical engineering

Subjects: Electrical engineering and electronics, Automated control systems, Architecture of ship's system.


Anatolii Afanasievich Gladkikh, Ulyanovsk State Technical University, Candidate of Engineering; graduated from the S.M. Budyonny Military Academy of Signal Corps; finished his post-graduate studies at the same academy; Professor at the Department of Telecommunication at Ulyanovsk State Technical University; an author of a monograph, textbooks, articles, and patents in the field of noiseless coding and information security. [e-mail: a.gladkikh@ulstu.ru]A. Gladkikh,

Nikolai Iurievich Chilikhin, Ulyanovsk State Technical University, graduated from Ulyanovsk State Technical University; finished his post-graduate studies at the same University; Lecturer at the Department of Telecommunication at Ulyanovsk State Technical University; an author of articles in the field of noiseless coding and information security. [e-mail: n.chilikhin@gmail.com]N. Chilikhin,

Sergei Mikhailovich Namestnikov, Ulyanovsk State Technical University, Candidate of Engineering; graduated from Ulyanovsk State Technical University, finished his post-graduate studies at the same university; Associate Professor at the Department of Telecommunication at Ulyanovsk State Technical University; an author of articles in the field of statistical signal processing. [e-mail: sernam@ulstu.ru]S. Namestnikov,

Dmitrii Vladimirovich Ganin, Nizhny Novgorod State Agricultural Academy, Candidate of Economics, Associate Professor; graduated from Nizhny Novgorod State Agricultural Academy; Head of the Department of Infocommunication Technologies and Telecommunications at the Nizhny Novgorod State University of Engineering and Economics; an author of articles in the field of infocommunications. [e-mail: ngiei135@mail.ru]D. Ganin

Unification of Redundant Code Decoding Algorithms in Integrated Information-management Systems 39_2.pdf

The increasing requirements for control of integrated information-management system elements are caused by the need of application of communication protocols that are heterogeneous in terms of organization and control cycle duration. Thereupon, it is reasonable to use a set of error-controlled codes differing in redundancy, and processed on a common hardware platform, in similar systems to prevent errors in real-time information. To implement this concept it is expedient to use short block codes. They are applicable in the process of small data transmitting and they can be easily transformed to protect a large bulk of data using the cascaded coding technology or on the basis of product codes in 3D or in higher dimensions. The code sequences shortening at specified requirements in terms of data adequacy leads to a need of the flexible synthesis of information on signals received from a continuous communications channel and of soft iterative algorithms of the selected redundant codes processing. Polar code constructions meet this requirement. The paper offers to use the proper code combinations space clustering in order to reduce the polar code combinations processing time interval. The text gives valuable information on a clustering mechanism and cluster number security variants when transmitting over a noisy channel. The authors present the results of polar code decoding simulation models testing using different algorithms that demonstrate the benefits of the proposed data processing method under conditions of low signal-to-noise ratios compared to canonical schemes required for redundant code decoding.

Polar code, soft-decision decoder, iterative process, cluster, cascade code, erasure, list decoding.

2015_ 1

Sections: Automated control systems

Subjects: Automated control systems, Electrical engineering and electronics, Architecture of ship's system.


Vyacheslav Viktorovich Epifanov, Ulyanovsk State Technical University, Doctor of Engineering; graduated from the Faculty of Machine-Building of Ulyanovsk Polytechnic Institute; Professor at the Department of Motorcars of Ulyanovsk State Technical University; an author of monographs, articles, and inventions in the field of process engineering of numerically controlled metal-cutting machine tools. [e-mail: v.epifanov73@mail.ru]V. Epifanov

Automated Grouping of Machine Components Such As Rotation Bodies Using Cluster Analysis 38_14.pdf

In a multiproduct batch production the technological basis for the computer numerical control (CNC) machine tools engineering can only be a properly selected group of parts. Therefore, on the basis of the cluster analysis application a methodology is developed which enables to quantify the similarity of the parts based on constructive and technological characteristics and to implement the parts sections. As a objective function (or as a grouping criterion) a following condition is adopted: a maximal usage of at least one CNC machine processing parts of a particular group for a year.In practice, the method is implemented in terms of a regional components data bank, which contains the information about 130 thousand types of parts. The calculations of the distances between clusters are performed on PC by means of a software product ‘STATISTIKA’, which enables to get a result automatically in a form of a dendrogram after the initial data is intro-duced. The dendrogram shows an optimal sequence of all clusters unification. As a result of calculations, nine groups of parts are formed which meet the objective function and which are appropriate to use as a process basis of the design of the range of advanced CNC-lathe machines. The specification requirements for the engineering of the range of advanced CNC-lathe machines are coordinated with the machine-tool enterprises of Moscow, Samara, and Ulyanovsk.

Part, group, machine, cluster, classification feature.

2014_ 4

Sections: Computer-aided engineering

Subjects: Computer-aided engineering.


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