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«INFORMATICS AND APPLICATIONS»
Scientific journal
Volume 19, Issue 4, 2025
Content | About Authors
Abstract and Keywords
- A. V. Borisov Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
Abstract: The paper is devoted to the problem of optimal state filtering for a class of special Markov jump processes.
The system consists of two coupled components. The first component is a Markov jump process with a finite state space. The second component evolves synchronously with the first one and, given the trajectory of the first component, forms a sequence of independent random vectors. The observations are modeled by a diffusion process whose drift and diffusion coefficients depend on the underlying state to be estimated. The filtering problem is to determine the conditional distribution of the system state given the available observations. Through a suitable transformation, the original observations can be reduced to a diffusion process with unit diffusion accompanied by a function of the system state observed without noise. The conditional probability distribution of the state is absolutely continuous with respect to a specially constructed reference measure. Its conditional density is characterized by a system of recurrently connected stochastic integrodifferential equations - essentially, a variant of the Kushner-Stratonovich equation - augmented by integral transformations.
Keywords: special Markov jump process; observations with multiplicative noise; conditional probability density function; Kushner-Stratonovich equation
- A. V. Bosov Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
- I. V. Uryupin Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
Abstract: The paper examines the variants of unstable operation of the extended Kalman filter (EKF). The set of experiments was performed with a typical model of a stochastic observation system. The motion of an autonomous object with a constant average velocity was modeled under conditions of uncontrolled velocity perturbations forming a chaotic trajectory with a regular target direction. Observations of two independent complexes consist of measurements of bearing angles (azimuth and elevation angle) and range. The estimation of the object's position is performed by the basic EKF and its modification using the method of linear pseudoobservations. The basic EKF turns out to be unstable in the initial model. The EKF uses the method of pseudomeasurements to provide a stable assessment of the position with high accuracy. The purpose of the experiments is to show which changes in the monitoring system model led to unstable operation of this EKF modification. For this purpose, 4 scenarios have been proposed, calculated, and analyzed: (i) inaccurate detection of the initial position; (ii) inability to identify the speed parameters in advance; (iii) movement with an abrupt change in speed parameters while maintaining the direction of the target; and (iv) inaccurate setting of statistical characteristics (covariance) of measurement errors. In each of the scenarios, the EKF turns out to be unstable, forming an estimate of the object's position with unacceptable accuracy. At the same time, the nature of instability and the behavior of the EKF estimates are different as demonstrated by numerical and graphical calculation results.
Keywords: stochastic filtering; discrete stochastic observation system; extended Kalman filter (EKF); EKF by the method of linear pseudomeasurement
- E. A. Machnev RUDN University, 6 Miklukho-Maklaya Str., Moscow 117198, Russian Federation
- U. K. Morozova RUDN University, 6 Miklukho-Maklaya Str., Moscow 117198, Russian Federation
- V. A. Beschastnyi RUDN University, 6 Miklukho-Maklaya Str., Moscow 117198, Russian Federation
- V. S. Shorgin Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
- Yu. V. Gaidamaka RUDN University, 6 Miklukho-Maklaya Str., Moscow 117198, Russian Federation, Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
Abstract: Integrated Access and Backhaul (IAB) technology standardized by the 3GPP provides the possibility to significantly reduce the cost of 5G New Radio deployments. The authors study the transmission delay in dense urban areas operating in the millimeter frequency range. The proposed system model allows for buffering analysis at transit IAB-nodes using the queuing theory and includes parameterization of the radio channel using the methods of stochastic geometry. The numerical experiment showed that the system performance in terms of packet delay and resource utilization is determined mainly by road traffic conditions and not by the coverage area of IAB-nodes.
Keywords: 5G New Radio; latency; queue
- M. G. Konovalov Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
- R. V. Razumchik Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
Abstract: A single flow of customers arrives to the two-phase tandem queueing system. The first phase is the infinite-server queue which models the individual customer's delay. The second phase consists of N identical single server infinite capacity queues running in parallel. Upon arrival of a customer, the dispatcher must immediately decide which queue of the second phase will serve it. The dispatcher has certain a priori static information about the system and the incoming flow but the dynamic information about the queues arrives with a random delay.
A heuristic server allocation procedure is proposed that utilizes delayed information and the dispatcher's own decision history The algorithm is based on a combination of two techniques commonly used in dispatching problems: reserving queues for customers of a certain size and preferentially selecting servers with the shortest queue. The proposed procedure can be easily implemented in practice and does not require hardware changes. Numerical results comparing the new procedure with the most commonly used algorithms are presented.
Keywords: parallel service systems; dispatching; load balancing; delayed information; redundancy
- N. A. Dragunov Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
- E. V. Djukova Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
Abstract: The authors consider the issues of creating algorithmic support for supervised classification problem which is the one of the central tasks of machine learning. Original procedures of logical analysis and classification of integer data represented as a set of elements of Cartesian product of finite partially ordered sets (product of partial orders) are constructed and investigated. At the training stage of the proposed procedures, the search for so-called regular representative elementary classifiers (special fragments in feature descriptions of precedents that distinguish objects belonging to different classes) is performed. An asymptotically optimal algorithm for enumerating the required elementary classifiers over a product of antichains is constructed and the results of its testing on real-world tasks are presented. Theoretical and experimental justifications for the efficiency of the new classification procedures are provided for the case when linear orders on sets of feature values are defined.
The theoretical conclusions are based on the study of the metric (quantitative) properties of the set of regular representative elementary classifiers.
Keywords: supervised classification; correct logical classifier; regular representative elementary classifier; partially ordered data; Cartesian product of partial orders; metric (quantitative) properties of the set of elementary classifiers
- G. A. Chumarin Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation, M. V Lomonosov Moscow State University, 1-52 Leninskie Gory, Moscow 119991, GSP-1, Russian Federation
Abstract: The work proposes a method for restoring damaged regions of color three-channel images (the inpainting problem) based on the equation of nonlinear anisotropic diffusion. As the numerical solution algorithm, the lattice Boltzmann equation with five discrete velocities and multiple relaxation times is employed. The direction and intensity of the smoothing are determined using the structure matrix. A parallel implementation of the algorithm has been developed using MPI (Message Passing Interface) technology with image domain decomposition in a Cartesian topology. The application of the proposed method to images with defects of various shapes and sizes is examined. The results demonstrate the correctness of structural and color information restoration in the damaged regions. The accuracy of the method is evaluated on a test set of 10,000 images, and the execution times of sequential and parallel versions of the algorithm are compared.
Keywords: image restoration; inpainting; lattice Boltzmann equations; anisotropic diffusion
- S. V. Ivanov Moscow Aviation Institute (National Research University), 4 Volokolamskoe Shosse, Moscow 125933, Russian Federation
- Ya. G. Martyushova Moscow Aviation Institute (National Research University), 4 Volokolamskoe Shosse, Moscow 125933, Russian Federation
- A. V. Naumov Moscow Aviation Institute (National Research University), 4 Volokolamskoe Shosse, Moscow 125933, Russian Federation
- A. E. Stepanov Moscow Aviation Institute (National Research University), 4 Volokolamskoe Shosse, Moscow 125933, Russian Federation
Abstract: The problem of building optimal program and positional strategy in dynamic model of passing time- limited test is considered. The tester sequentially solves the test tasks, gaining a certain number of points for each task in case of the correct solution. The correctness of the test of each task is modeled by a random variable with a Bernoulli distribution. The time spent on solving each task is also considered to be random. The positional strategy is a function of the number of points scored after solving the next task and the total time spent on solving previous test tasks. The function takes the value one if the tester solves the next task and zero if misses. The criterion is the number of points scored for the test, the excess of which, while simultaneously fulfilling the limit on the test execution time, is guaranteed with a predetermined level of confidence which acts as a task parameter. To solve the problems under consideration, the equivalence property is used between the problem with the quantile criterion and the problem of maximizing the corresponding probability function. After that, a modification of the algorithm for solving a similar problem with a probabilistic quality criterion proposed earlier by the authors is used.
Keywords: time-limited test; dynamic model; positional strategy; quantile criterion
- A. A. Grusho Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
- N. A. Grusho Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
- M. I. Zabezhailo Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
- V. V. Kulchenkov VTB Bank, 43-1 Vorontsovskaya Str., Moscow 109147, Russian Federation
- E. E. Timonina Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
Abstract: The usage of cause-and-effect relationships to classify small data sets of high dimension can generate conflicts due to the fact that a significant part of the data does not play a significant role in the classification task and can be considered as random data. In this case, in terms of cause-and-effect relationships, random data can generate pieces ofinformation that interfere with correct classification or generate classification errors. Additional information is needed to neutralize characteristics errors. In the present paper, such additional information was also found using causal relationships. The authors define indirect characteristics that can be used to resolve conflicts and to refine the classification. Using the task ofclassifying ofthree informative classes as an example, it is shown how to obtain and how to use indirect characteristics to resolve conflict situations during the classification process and error prevention process.
Keywords: classification; cause-and-effect relationships; indirect characteristics of correct classification
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