Труды сотрудников ИВМ СО РАН

/ V. A. Gerasimov, B. S. Dobronets, M. Yu. Shustrov // Avtomatika i Telemekhanika. - 1991. - Is. 2. - P83-88 . - ISSN 0005-2310
Аннотация: Main principles of numerical arithmetical operations on histograms of random values are considered. A set of operations is defined including summing, subtracting, multiplication, division, rising to an integer power, maximum, and minimum. It is stated that this set is sufficient to calculate any function of an independent random value. A PASCAL program package is introduced implementing histogram arithmetic. Several applications of the package are mentioned.

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Держатели документа:
Vychislitel'nyj Tsentr Sibirskogo, Otdeleniya AN SSSR, Krasnoyarsk, Russian Federation
ИВМ СО РАН

Доп.точки доступа:
Gerasimov, V.A.; Dobronets, B.S.; Добронец, Борис Станиславович; Shustrov, M.Yu.

[Текст] : статья / А. В. Лапко, В. А. Лапко // Информатика и системы управления. - 2016. - № 3. - С. 78-85, DOI 10.22250/isu.2016.49.78-85 . - ISSN 1814-2400
   Перевод заглавия: PERFORMANCE ANALYSIS OF DISCRETIZATION TECHNIQUES OF TWO-DIMENSIONAL FIELD OF VALUES OF A RANDOM VARIABLE IN THE SYNTHESIS OF A NONPARAMETRIC ESTIMATE OF PROBABILITY DENSITY

УДК

519.7

Аннотация: Проводится сравнение оптимального и эвристических методов дискретизации области значений двумерной случайной величины. Определяются условиях их компетенции при восстановлении нормального закона распределения двух независимых случайных величин. Эффективность методики подтверждается результатами вычислительных экспериментов.
The paper gives wide coverage to comparison of optimal and heuristic discretization techniques of two-dimensional field of values of a random variable. It defines the terms of their competency under restoration of normal law of distribution of two independent random variables. The efficiency of the method is confirmed by the results of computational experiments.

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Держатели документа:
Институт вычислительного моделирования СО РАН
Сибирский государственный аэрокосмический университет им. академика М.Ф. Решетнева

Доп.точки доступа:
Лапко, Василий Александрович; Lapko V.A.; Lapko A.V.

[Text] / A. V. Lapko, V. A. Lapko // Meas. Tech. - 2017. - Vol. 60, Is. 4. - P325-330, DOI 10.1007/s11018-017-1196-1. - Cited References:9. - This work was conducted within the design section of State Assignment of the Ministry of Education and Science of Russia No. 2.914.2014/K and the Program of the Siberian Branch of the Russian Academy of Sciences IV.35.1. . - ISSN 0543-1972. - ISSN 1573-8906РУБ Engineering, Multidisciplinary + Instruments & Instrumentation

Аннотация: Optimal and heuristic methods of digitizing the range of values of a two-dimensional random variable are compared. Conditions of the scope of these methods are defined in re-establishing the normal law of distribution of two dependent random variables. Results of computational tests are examined.

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Держатели документа:
RAS, SB, ICM, Krasnoyarsk, Russia.
Reshetnev Siberian State Aerosp Univ, Krasnoyarsk, Russia.

Доп.точки доступа:
Lapko, A. V.; Lapko, V. A.; Program of the Siberian Branch of the Russian Academy of Sciences [IV.35.1]

/ A. V. Lapko, V. A. Lapko, E. A. Yuronen // 2017 International Siberian Conference on Control and Communications, SIBCON 2017 - Proceedings. - 2017. - 2017 International Siberian Conference on Control and Communications, SIBCON 2017 (29 June 2017 through 30 June 2017, ) Conference code: 129746, DOI 10.1109/SIBCON.2017.7998533 . -
Аннотация: Optimum and heuristic sampling methods of a range of values of a two-dimensional random value are investigated. Conditions of their competence at recovery of the normal distribution law of two independent random values are defined. © 2017 IEEE.

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Держатели документа:
Institute of Computer Modelling SB RAS, Reshetnev Siberian State Aerospace University, Krasnoyarsk, Russian Federation
Reshetnev Siberian State Aerospace University, Siberian Federal University, Krasnoyarsk, Russian Federation

Доп.точки доступа:
Lapko, A. V.; Lapko, V. A.; Yuronen, E. A.

: статья / А. В. Лапко, В. А. Лапко // Измерительная техника. - 2018. - № 5. - С. 9-13 . - ISSN 0368-1025

УДК

519.24

Аннотация: Рассмотрены методы оценивания параметров формулы оптимальной дискретизации области определения плотности вероятности двумерной случайной величины. Исследованы свойства свойства предложенных методов и определены условия их компетентности.
Methods for estimating the parameters of the formula for the optimal discretization of the range of variation in the probability density of a two-dimensional random variable are considered. The properties of the proposed methods are investigated and the conditions for their competence are defined.

РИНЦ

Держатели документа:
Институт вычислительного моделирования Сибирского отделения РАН
Сибирский государственный университет науки и технологий им. акад. М.Ф. Решетнева

Доп.точки доступа:
Лапко, А.В.; Лапко, В.А.

: статья / Александр Николаевич Мацулев, Константин Васильевич Симонов // Информатизация и связь. - 2018. - № 3. - С. 24-30 . - ISSN 2078-8320
   Перевод заглавия: Analysis of external geophysical factors connecting strong earthquake

УДК

550.34

Аннотация: Исследование посвящено анализу сейсмической активности Земли с целью поиска закономерностей, связанных с внешними космическими факторами, циклическими по своей природе. На основе гистограммного подхода, с применением Фурье- и вейвлет-анализа изучаются особенности связи астрономических явлений (фаза Луны и др.) и проявлений сильных землетрясений, а также с глобальной сейсмичностью.
The study is devoted to the analysis of the Earth ’s seismic activity in order to search for regularities related to external cosmic factors, cyclic in nature. On the basis of the histogram approach, using Fourier and wavelet analysis, the features of the connection of astronomical phenomena (the phase of the Moon, etc.) and manifestations of strong earthquakes, with global seismicity are studied.

РИНЦ

Держатели документа:
Институт вычислительного моделирования СО РАН

Доп.точки доступа:
Мацулев, Александр Николаевич; Matsulev Alexander Nikolaevich; Симонов, Константин Васильевич; Simonov Konstantin Vasilyevich

[Текст] : статья / Елена Васильевна Тицкая [и др.] // Медицина и высокие технологии. - 2018. - № 4. - С. 56-64 . - ISSN 2306-3645
   Перевод заглавия: ANALYSIS OF THE EXPERIMENTAL DATA OF POSTOPERATIVE REMODELING OF THE SHOULDER BY CON-TREX

УДК

616.727.2

Аннотация: Изучены возможности применения роботизированной механотерапии на комплексе Con-trex в восстановительном лечении пациентов после артроскопических реконструктивных операций на плечевом суставе. Выполнены анализ статистики и моделирование данных, полученных в ходе экспериментальных исследований. На этой основе разработаны элементы методики для повышения эффективности и ускорения процесса реабилитации.
The possibilities of using robotic mechanotherapy on the Con-trex complex in the rehabilitation treatment of patients after arthroscopic reconstructive operations on the shoulder joint have been studied. The analysis of statistics and modeling of data obtained in the course of experimental studies. On this basis, developed elements of the methodology to improve the efficiency and speed up the rehabilitation process.

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Держатели документа:
Институт вычислительного моделирования СО РАН
Филиал ТНИИКиФ ФГБУ СибФНКЦ ФМБА
Центр восстановительной медицины ФГБУ ФСНКЦ ФМБА России

Доп.точки доступа:
Тицкая, Елена Васильевна; Titskaya Elena Vasilyevna; Кабаев, Евгений Михайлович; Kabaev Evgeny Mikhailovich; Мацулев, Александр Николаевич; Matsulev Alexander Nikolaevich; Симонов, Константин Васильевич; Simonov Konstantin Vasilyevich

/ A. V. Lapko [et al.] // Optoelectron. Instrum. Data Proc. - 2019. - Vol. 55, Is. 3. - P230-236, DOI 10.3103/S8756699019030038. - Cited References:18. - This work was supported by the Russian Foundation for Basic Research (Grant No. 18-01-00251). . - ISSN 8756-6990. - ISSN 1934-7944РУБ Physics, Multidisciplinary

Аннотация: A nonparametric algorithm of automatic classification of large arrays of statistical data is considered. Its synthesis is based on decomposition of initial data. The results of decomposition form a set of centers of multidimensional intervals and the corresponding frequencies of occurrence of values of random variables. Based on information obtained, classes corresponding to single-mode fragments of the probability density of features of examined objects are detected. The spatial interpretation of automatic classification results is analyzed. The nonparametric algorithms developed in the study are important tools of processing of data obtained by remote sensing of natural resources.

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Держатели документа:
Russian Acad Sci, Siberian Branch, Inst Computat Modeling, Akademgorodok 50,Bldg 44, Krasnoyarsk 660036, Russia.
Russian Acad Sci, Siberian Branch, Sukachev Inst Forest, Akademgorodok 50,Bldg 28, Krasnoyarsk 660036, Russia.
Reshetnev Siberian Univ Sci & Technol, Pr Im Gazety Krasnoyarskii Rabochii 31, Krasnoyarsk 660037, Russia.

Доп.точки доступа:
Lapko, A. V.; Lapko, V. A.; Im, S. T.; Tuboltsev, V. P.; Avdeenok, V. A.; Russian Foundation for Basic Research [18-01-00251]

/ A. V. Lapko, V. A. Lapko // Meas. Tech. - 2019, DOI 10.1007/s11018-019-01690-2 . - Article in press. - ISSN 0543-1972
Аннотация: The dependence between the sampling interval of the domain of values of a one-dimensional random variable and the blur coefficient of the kernel probability density estimate is determined. The studies used the results of an analysis of the asymptotic properties of a nonparametric estimate of the probability density of the Rosenblatt–Parzen type and its modification. It is shown that the modification of the kernel probability density estimate is a smoothed histogram. The optimal expressions for the kernel function blur coefficient and the length of the sampling interval of the domain of values of a one-dimensional random variable are considered. These parameters are obtained from the condition of minimum mean square deviations of the considered probability density estimates. On this basis, a relationship was established between the studied parameters, which is determined by a constant and depends on the applied kernel function and the volume of the initial statistical data. The values of the detected constant are characterized by the form of the reconstructed probability density and are independent of its parameters. According to the data of computational experiments, formulas are proposed for estimating the analyzed constant by the value of the antikurtosis coefficient for symmetric and asymmetric distribution laws. To estimate the antikurtosis coefficient, we used the initial statistical data in the problem of reconstructing the probability density. The results obtained make it possible to quickly determine the length of the sampling interval from the value of the kernel function blur coefficient, which is relevant when testing hypotheses about the distributions of random variables. The presented conclusions are confirmed by the results of computational experiments. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

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Держатели документа:
Institute of Computational Modeling, Siberian Branch of the Russian Academy of Sciences, Krasnoyarsk, Russian Federation
Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russian Federation

Доп.точки доступа:
Lapko, A. V.; Lapko, V. A.

/ Y. Hamad, O. K.J. Mohammed, K. Simonov // ACM International Conference Proceeding Series : Association for Computing Machinery, 2019. - 9th International Conference on Information Systems and Technologies, ICIST 2019 (24 March 2019 through 26 March 2019, ) Conference code: 154766. - Ст. a22, DOI 10.1145/3361570.3361598 . -
Аннотация: The emerging field of in cancer pathology (computational pathology) using histological images of biopsies is a computer aided diagnosis. This paper devoted to computational methods for assessing the indicators of the process of tissue regeneration with the release of nickel-mesh reticulated titanium implants with shape memory. Accordingly, in order to design such computer-aided system that is able to measure the implants size and growth rate, this paper presents a computational toolkit. Moreover, this toolkit used to analyze the dynamics of the process and highlight the internal geometric features of the experimental images (segmentation algorithms and visualization of spatial data). The computational tools for preprocessing visual data is the important concept solution to increase the contrast and brightness of the analyzed images based on the Contrast Limited Adaptive Histogram Equalization (CLAHE). Finally, the result of proposed technique shows that the increasing the accuracy of estimates for testing data through (15-20%). © 2019 Association for Computing Machinery.

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Держатели документа:
Institute of Space and Information Technology, Siberian Federal University, Krasnoyarsk, Russian Federation
Dir. of Computer Center, University of Fallujah, Iraq
Institute of Computational Modeling, Siberian Branch, Russian Academy of Sciences, Krasnoyarsk, Russian Federation

Доп.точки доступа:
Hamad, Y.; Mohammed, O. K.J.; Simonov, K.

/ A. Zotin [et al.] // Procedia Computer Science : Elsevier B.V., 2019. - Vol. 159: 23rd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, KES 2019 (4 September 2019 through 6 September 2019, ) Conference code: 141548. - P1642-1651, DOI 10.1016/j.procs.2019.09.334 . -
Аннотация: The paper is devoted to the analysis of the features of the EWH parameter change over the geoid using satellite measurements of the GRACE space system. These local gravitational anomalies are studied depending on the geometrical characteristics of the focal zones of the strongest underwater earthquakes in the period 2003-2016. The statistical processing of satellite observations data using the histogram and maximum entropy methods was performed. Completed interpretation and obtained estimates showing differences and similarities in observational data, due to the peculiarities of the structure of the studied geomedia and the corresponding focal areas. The final result is a statistical description of the space of anomalies of the gravitational field of the Earth as a whole and features of local gravitational anomalies over the focal zones of underwater strong earthquakes in the period from 2003 to 2016. © 2019 The Author(s). Published by Elsevier B.V.

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Держатели документа:
Reshetnev Siberian State University of Science and Technology, 31 Krasnoyarsky rabochy av., Krasnoyarsk, 660037, Russian Federation
Institute of Computational Modeling SB RAS, 50/44 Akademgorodok, Krasnoyarsk, 660036, Russian Federation
Institute of Chemistry and Chemical Technology SB RAS, 50/24 Akademgorodok, Krasnoyarsk, 660036, Russian Federation
Siberian Federal University, 79 Svobodny st., Krasnoyarsk, 660041, Russian Federation

Доп.точки доступа:
Zotin, A.; Simonov, K.; Matsulev, A.; Kurako, M.

/ A. V. Lapko, V. A. Lapko // Meas. Tech. - 2020. - Vol. 62, Is. 11. - P945-952, DOI 10.1007/s11018-020-01717-z. - Cited References:15 . - ISSN 0543-1972. - ISSN 1573-8906РУБ Engineering, Multidisciplinary + Instruments & Instrumentation

Аннотация: The dependencies between the sampling intervals of the domain of values of a multidimensional random variable and the blur coefficients of the kernel probability density estimate are determined. The results of an analysis of the asymptotic properties of a multidimensional nonparametric estimate of the probability density of the Rosenblatt-Parzen type and its modifications are investigated. Modification of the kernel probability density estimate is a smoothed multi-dimensional histogram. The formulas for calculating the optimal parameters of the kernel function blur coefficients and the lengths of the sampling intervals of the values of the components of a multidimensional random variable are analyzed. Blur coefficients are presented as the products of an indefinite parameter and the mean square deviations of random components. An indefinite parameter and the number of sampling intervals of multidimensional random variables are found from the condition of minimum mean square deviations of the considered probability density estimates. Based on the results obtained, the relationships between the blur coefficient parameters and the discretization procedure of the range of values of a multidimensional random variable are established. The discovered patterns are characterized by a set of constants. The constants under consideration are represented by the ratio of nonlinear functionals of the probability density and their second derivatives with respect to each random component. The values of the constants are characterized by the type of probability density and are independent of their parameters. From computational experimental data, we establish the relationships between the constants and the product of the counterexcess coefficients with the components of a multidimensional random variable. The results obtained make it possible to quickly determine the lengths of sampling intervals of the values of the components of a multidimensional random variable from the kernel function blur coefficients of a nonparametric probability density estimate.

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Держатели документа:
Russian Acad Sci, Siberian Branch, Inst Computat Modeling, Krasnoyarsk, Russia.
Reshetnev Siberian State Univ Sci & Technol, Krasnoyarsk, Russia.

Доп.точки доступа:
Lapko, A. V.; Lapko, V. A.