13 research outputs found

    Использование апостериорной информации при реализации систем радиолокационного распознавания с применением нейросетевых технологий

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    Introduction. The current need to obtain relevant, complete and reliable information about airborne objects has led to the continuous improvement of modern radar recognition systems (MRRS) as part of control systems. The development of modern MRRS has created objective prerequisites for the use of progressive and new methods and algorithms for the processing of signals using neural networks. The use of artificial neural networks with learning ability permits expansion to include many signs of recognition by using information obtained in the process of monitoring airspace.Aim. To formulate the problem and develop proposals for the use of posterior information for airspace control in radar recognition systems using neural network technologies.Materials and methods. Based on an analysis of the structure of a unified information network, an approach was formulated to facilitate the development of MRRS based on training technologies. Using the synthesis method, examples of technical solutions were proposed, which will allow the use of modern methods and signal processing algorithms using a posteriori information generated by the control system.Results. The study identified the principles of neural network training in solving the recognition problem in the process of functioning of radio electronic equipment (REE). The technical solutions pro-posed take the functioning of the integrated radar system into account, allowing the information parameters required for training MRRS in a single information field to be obtained. It is shown that the removal of restrictions associated with the functional autonomy of REE, allows the use of posterior information in the implementation of radar recognition systems. This also allows for an increase in the number of recognition signs used in the algorithms and for the database of portraits to be replenished. Conclusion. MRRS can be developed via training by removing the restrictions associated with the autonomous functioning of RES. This allows for the situational assessment to be enhanced and management decisions to be optimised.Введение. Существующая в настоящее время необходимость получения актуальной, полной и достоверной информации о воздушных объектах определяет постоянное совершенствование современных систем радиолокационного распознавания (СРЛР), входящих в состав систем управления. Развитие современных СРЛР создает объективные предпосылки для использования прогрессивных и разработки новых методов и алгоритмов обработки сигналов с помощью нейронных сетей. Применение искусственных нейронных сетей, обладающих свойством обучаемости, позволяет расширить множество признаков распознавания за счет использования полученной в процессе контроля воздушного пространства информации.Цель работы. Формулировка задачи и разработка предложений по использованию апостериорной информации для контроля воздушного пространства в системах радиолокационного распознавания при применении нейросетевых технологий.Материалы и методы. На основе анализа структуры единого информационного пространства сформулирован подход к развитию СРЛР на основе обучающих технологий. С применением метода синтеза предложены примеры технических решений, позволяющие использовать современные методы и алгоритмы обработки сигналов на основе апостериорной информации, формируемой системой управления.Результаты. Сформулированы принципы обучения нейронной сети при решении задачи распознавания в процессе функционирования радиоэлектронных средств (РЭС). Предложены технические решения, учитывающие функционирование интегрированной радиолокационной системы и позволяющие в едином информационном поле получать требуемые для обучения СРЛР информационные параметры. Показано, что снятие ограничений, связанных с автономностью функционирования РЭС, позволяет использовать апостериорную информацию при реализации систем радиолокационного распознавания. Этот факт дает возможность увеличить количество используемых в алгоритмах признаков распознавания и пополнить базы портретов.Заключение. СРЛР может развиваться посредством обучения за счёт снятия ограничений, связанных с автономностью функционирования РЭС. Это позволяет повысить адекватность оценки обстановки и оптимизировать принимаемые управленческие решения

    Use of Aposteriori Information in the Implementation of Radar Recognition Systems Using Neural Network Technologies

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    Introduction. The current need to obtain relevant, complete and reliable information about airborne objects has led to the continuous improvement of modern radar recognition systems (MRRS) as part of control systems. The development of modern MRRS has created objective prerequisites for the use of progressive and new methods and algorithms for the processing of signals using neural networks. The use of artificial neural networks with learning ability permits expansion to include many signs of recognition by using information obtained in the process of monitoring airspace.Aim. To formulate the problem and develop proposals for the use of posterior information for airspace control in radar recognition systems using neural network technologies.Materials and methods. Based on an analysis of the structure of a unified information network, an approach was formulated to facilitate the development of MRRS based on training technologies. Using the synthesis method, examples of technical solutions were proposed, which will allow the use of modern methods and signal processing algorithms using a posteriori information generated by the control system.Results. The study identified the principles of neural network training in solving the recognition problem in the process of functioning of radio electronic equipment (REE). The technical solutions pro-posed take the functioning of the integrated radar system into account, allowing the information parameters required for training MRRS in a single information field to be obtained. It is shown that the removal of restrictions associated with the functional autonomy of REE, allows the use of posterior information in the implementation of radar recognition systems. This also allows for an increase in the number of recognition signs used in the algorithms and for the database of portraits to be replenished. Conclusion. MRRS can be developed via training by removing the restrictions associated with the autonomous functioning of RES. This allows for the situational assessment to be enhanced and management decisions to be optimised

    Low Genetic Diversity in Wide-Spread Eurasian Liver Fluke <i>Opisthorchis felineus</i> Suggests Special Demographic History of This Trematode Species

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    <div><p></p><p><i>Opisthorchis felineus</i> or Siberian liver fluke is a trematode parasite (Opisthorchiidae) that infects the hepato-biliary system of humans and other mammals. Despite its public health significance, this wide-spread Eurasian species is one of the most poorly studied human liver flukes and nothing is known about its population genetic structure and demographic history. In this paper, we attempt to fill this gap for the first time and to explore the genetic diversity in <i>O. felineus</i> populations from Eastern Europe (Ukraine, European part of Russia), Northern Asia (Siberia) and Central Asia (Northern Kazakhstan). Analysis of marker DNA fragments from <i>O. felineus</i> mitochondrial <i>cytochrome c oxidase subunit 1</i> and <i>3</i> (<i>cox1, cox3</i>) and nuclear rDNA <i>internal transcribed spacer 1</i> (<i>ITS1</i>) sequences revealed that genetic diversity is very low across the large geographic range of this species. Microevolutionary processes in populations of trematodes may well be influenced by their peculiar biology. Nevertheless, we suggest that lack of population genetics structure observed in <i>O. felineus</i> can be primarily explained by the Pleistocene glacial events and subsequent sudden population growth from a very limited group of founders. Rapid range expansion of <i>O. felineus</i> through Asian and European territories after severe bottleneck points to a high dispersal potential of this trematode species.</p></div
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