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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">uprinmatus</journal-id><journal-title-group><journal-title xml:lang="ru">Известия Юго-Западного государственного университета. Серия: Управление, вычислительная техника, информатика. Медицинское приборостроение</journal-title><trans-title-group xml:lang="en"><trans-title>Proceedings of the Southwest State University. Series: IT Management, Computer Science, Computer Engineering. Medical Equipment Engineering</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2223-1536</issn><publisher><publisher-name>Юго-Западный государственный университет</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.21869/2223-1536-2022-12-4-177-191</article-id><article-id custom-type="elpub" pub-id-type="custom">uprinmatus-84</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>МОДЕЛИРОВАНИЕ В МЕДИЦИНСКИХ И ТЕХНИЧЕСКИХ СИСТЕМАХ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>MODELING IN MEDICAL AND TECHNICAL SYSTEMS</subject></subj-group></article-categories><title-group><article-title>Модель обработки информации в коэффициентной обратной задаче для алгебраического многочлена</article-title><trans-title-group xml:lang="en"><trans-title>Information Processing Model in the Coefficient Inverse Problem for an Algebraic Polynomial</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-1108-4185</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Локтионов</surname><given-names>А. П.</given-names></name><name name-style="western" xml:lang="en"><surname>Loktionov</surname><given-names>A. P.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Локтионов Аскольд Петрович,д-р технических наук, доцент</p><p>Researcher ID: P-5434-2015</p><p>ул. 50 лет Октября 94, г. Курск 305040</p></bio><bio xml:lang="en"><p>Askold P. Loktionov, Dr. of Sci. (Engineering), Associate Professor</p><p>Researcher ID: P-5434-2015</p><p>50 Let Oktyabrya Str. 94, Kursk 305040</p></bio><email xlink:type="simple">loapa@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Юго-Западный государственный университет</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Southwest State University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2022</year></pub-date><pub-date pub-type="epub"><day>12</day><month>05</month><year>2023</year></pub-date><volume>12</volume><issue>4</issue><fpage>177</fpage><lpage>191</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Локтионов А.П., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Локтионов А.П.</copyright-holder><copyright-holder xml:lang="en">Loktionov A.P.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://uprinmatus.elpub.ru/jour/article/view/84">https://uprinmatus.elpub.ru/jour/article/view/84</self-uri><abstract><p>Цель исследования заключается в разработке модели описания и оценки эффективности решения коэффициентной обратной задачи анализа и обработки информации об алгебраическом многочлене с заданными коэффициентами членов младших степеней в условиях влияния погрешности входных данных на точность решения.</p><sec><title>Методы</title><p>Методы. В качестве базового математического аппарата используется методология решения обратных задач с приближением функций интерполяционным полиномом Лагранжа. В условиях равномерной непрерывной нормы погрешности входных данных при оценке эффективности решения коэффициентной обратной задачи предлагается использовать минимальное значение целевой функции в виде минимума функции Лебега. При выводе явных формул оптимального плана координат узлов сетки аппроксимации предлагается применить альтернансную характеристику экстремального полинома.</p></sec><sec><title>Результаты</title><p>Результаты. В качестве базовых элементов математической модели анализа и обработки информации об алгебраическом многочлене в решении коэффициентной обратной задачи использованы интерполяционные полиномы Лагранжа с числовой оценкой эффективности решения по значению минимума функции Лебега при оптимальном плане координат узлов сетки аппроксимации.</p></sec><sec><title>Заключение</title><p>Заключение. В ходе проводимых исследований решалась задача разработки модели описания и оценки эффективности решения коэффициентной обратной задачи анализа и обработки информации об алгебраическом многочлене с частично заданными коэффициентами членов младших степеней и с влиянием погрешности входных данных на точность решения. Показано, что для количественной оценки эффективности решения задачи следует использовать значение целевой функции в виде минимума функции Лебега с вычислением коэффициентов приближенного многочлена интерполяционным полиномом Лагранжа. Для повышения точности распределения координат узлов сетки аппроксимации получены явные формулы оптимального плана координат путем построения экстремального полинома степени, равной степени исследуемого алгебраического многочлена, с числом точек чебышёвского альтернанса, совпадающим со степенью полинома.</p></sec></abstract><trans-abstract xml:lang="en"><p>The purpose of research is to develop a model for describing and evaluating the effectiveness of solving the coefficient inverse problem of analyzing and processing information about an algebraic polynomial with given coefficients of terms of lower degrees under the influence of input data error on the solution efficiency.</p><sec><title>Methods</title><p>Methods. As a basic mathematical apparatus, the methodology for solving inverse problems with the approximation of functions by the Lagrange interpolation polynomial is used. Under the conditions of a uniform continuous error rate of the input data, when evaluating the efficiency of solving the coefficient inverse problem, it is proposed to use the minimum value of the objective function in the form of the minimum of the Lebesgue function. When deriving explicit formulas for the optimal plan of coordinates of the nodes of the approximation grid, it is proposed to apply the alternance characteristic of the extremal polynomial.</p></sec><sec><title>Results</title><p>Results. As the basic elements of a mathematical model for analyzing and processing information about an algebraic polynomial in solving a coefficient inverse problem, Lagrange interpolation polynomials were used with a numerical estimate of the solution efficiency by the value of the minimum of the Lebesgue function.</p></sec><sec><title>Conclusion</title><p>Conclusion. In the course of the research, we solved the problem of developing a model for describing and evaluating the efficiency of the coefficient inverse problem of analyzing and processing information about an algebraic polynomial with given coefficients of terms of lower degrees and with the influence of the input data error on the accuracy of the solution. It is shown that to quantify the effectiveness of solving the problem, one should use the value of the objective function in the form of the minimum of the Lebesgue function, and to calculate the coefficients of the approximate polynomial, use the Lagrange interpolation polynomial.</p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>целевая функция</kwd><kwd>обратная задача</kwd><kwd>интерполяционный полином Лагранжа</kwd><kwd>функция Лебега</kwd><kwd>экстремальные свойства полиномов</kwd></kwd-group><kwd-group xml:lang="en"><kwd>target function</kwd><kwd>inverse problem</kwd><kwd>Lagrange interpolation polynomial</kwd><kwd>Lebesgue function</kwd><kwd>extremal properties of polynomials</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Bakushinsky A. B., Kokurin M. M., Kokurin M. Yu. Regularization Algorithms for Ill- Posed Problems. 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