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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">trudyniisi</journal-id><journal-title-group><journal-title xml:lang="ru">Труды НИИСИ</journal-title><trans-title-group xml:lang="en"><trans-title>SRISA Proceedings</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2225-7349</issn><issn pub-type="epub">3033-6422</issn><publisher><publisher-name>НИЦ «КУРЧАТОВСКИЙ ИНСТИТУТ» - НИИСИ</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.25682/NIISI.2025.3.0001</article-id><article-id custom-type="elpub" pub-id-type="custom">trudyniisi-115</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>ИСКУССТВЕННЫЙ ИНТЕЛЛЕКТ И МАШИННОЕ ОБУЧЕНИЕ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING</subject></subj-group></article-categories><title-group><article-title>Формирование матрицы проводимостей с помощью кусочно-постоянных сигналов</article-title><trans-title-group xml:lang="en"><trans-title>Crossbar Array Programming Using Piecewise-Constant Signals</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Бесхлебнова</surname><given-names>Г. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Beskhlebnova</surname><given-names>G. A.</given-names></name></name-alternatives><email xlink:type="simple">beskhlebnova@niisi.ras.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Котов</surname><given-names>В. Б.</given-names></name><name name-style="western" xml:lang="en"><surname>Kotov</surname><given-names>V. B.</given-names></name></name-alternatives><email xlink:type="simple">v1111111k1111@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">НИЦ «Курчатовский институт» - НИИСИ, Москва<country>Россия</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>28</day><month>12</month><year>2025</year></pub-date><volume>15</volume><issue>3</issue><issue-title>ТРУДЫ НИИСИ. МАТЕМАТИЧЕСКОЕ И КОМПЬЮТЕРНОЕ МОДЕЛИРОВАНИЕ СЛОЖНЫХ СИСТЕМ: ТЕОРЕТИЧЕСКИЕ И ПРИКЛАДНЫЕ АСПЕКТЫ</issue-title><fpage>9</fpage><lpage>16</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Бесхлебнова Г.А., Котов В.Б., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Бесхлебнова Г.А., Котов В.Б.</copyright-holder><copyright-holder xml:lang="en">Beskhlebnova G.A., Kotov V.B.</copyright-holder><license 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://www.t-niisi.ru/jour/article/view/115">https://www.t-niisi.ru/jour/article/view/115</self-uri><abstract><p>Для формирования матрицы проводимостей массива переменных резисторов необходима процедура произвольного изменения проводимостей резисторов массива при использовании ограниченного числа управляющих сигналов — напряжений на проводниках структуры типа кроссбар. Поскольку число проводников значительно меньше числа резисторов, такая процедура должна быть многошаговой. На каждом шаге происходит изменение проводимостей целевых резисторов, число которых не больше числа управляющих сигналов. При этом неизбежно меняются проводимости и некоторых нецелевых резисторов. Соответствующие изменения необходимо компенсировать. В работе рассмотрена процедура записи с использованием в качестве управляющих сигналов высокочастотных кусочно-постоянных сигналов. На основе анализа с использованием модели простого резисторного элемента показана возможность формирования произвольной (в известных пределах) матрицы проводимостей. На каждом шаге формируется (изменяется) строка или столбец матрицы. Обсуждаются условия, обеспечивающие выполнимость и удобство такой процедуры.</p></abstract><trans-abstract xml:lang="en"><p>To program a crossbar array, we need to adjust the resistor conductance using a limited number of control signals, which are voltages applied to the crossbar lines. Since the number of lines is significantly smaller than the number of resistors, this is a multi-step procedure. At each step, the conductances of the selected resistors are adjusted. The number of such resistors is no greater than the number of control signals. This inevitably changes the conductivity of some half-selected resistors, too. These unwanted changes must be compensated for. We examined a crossbar programming procedure using high-frequency piecewise-constant control signals. Our analysis involved a simple resistive element model. We demonstrated that an arbitrary (within known limits) conductance matrix can be programmed. At each step, a row or column of the crossbar array is generated or adjusted. We discussed the feasibility and convenience of such a procedure.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>переменный резистор</kwd><kwd>кусочно-постоянный сигнал</kwd><kwd>резисторная матрица</kwd><kwd>матрица проводимостей</kwd></kwd-group><kwd-group xml:lang="en"><kwd>variable resistor</kwd><kwd>piecewise constant signal</kwd><kwd>resistor array</kwd><kwd>conductivity matrix</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">Kotov V.B., Beskhlebnova G.A. Specifics of Crossbar Resistor Arrays. // B. Kryzhanovsky et al. (Eds.). Advances in Neural Computation, Machine Learning, and Cognitive Research VI (NEUROINFORMATICS 2022). Studies in Computational Intelligence. Vol. 1064. Cham: Springer. 2023. PP. 292–304. https://doi.org/10.1007/978-3-031-19032-2_31.</mixed-citation><mixed-citation xml:lang="en">Kotov V.B., Beskhlebnova G.A. Specifics of Crossbar Resistor Arrays. // B. Kryzhanovsky et al. (Eds.). Advances in Neural Computation, Machine Learning, and Cognitive Research VI (NEUROINFORMATICS 2022). Studies in Computational Intelligence. Vol. 1064. Cham: Springer. 2023. PP. 292–304. https://doi.org/10.1007/978-3-031-19032-2_31.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Adamatzky A., Chua L. Memristor Networks. Springer International Publishing (2014).</mixed-citation><mixed-citation xml:lang="en">Adamatzky A., Chua L. Memristor Networks. Springer International Publishing (2014).</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Advances in Memristors, Memristive Devices and Systems. / Edited by S. Vaidyanathan and C. Volos. Springer International Publishing AG (2017).</mixed-citation><mixed-citation xml:lang="en">Advances in Memristors, Memristive Devices and Systems. / Edited by S. Vaidyanathan and C. Volos. Springer International Publishing AG (2017).</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Kim S. Ju, Kim S., Jang H.W. Competing memristors for brain-inspired computing. iScience 24, 101889, January 22, 2021.</mixed-citation><mixed-citation xml:lang="en">Kim S. Ju, Kim S., Jang H.W. Competing memristors for brain-inspired computing. iScience 24, 101889, January 22, 2021.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Kotov V.B., Beskhlebnova G.A. Generation of the Conductivity Matrix. // B. Kryzhanovsky et al. (Eds.). Advances in Neural Computation, Machine Learning, and Cognitive Research V (NEUROINFORMATICS 2021). Studies in Computational Intelligence. Vol. 1008. Cham: Springer. 2022. PP. 276-284.</mixed-citation><mixed-citation xml:lang="en">Kotov V.B., Beskhlebnova G.A. Generation of the Conductivity Matrix. // B. Kryzhanovsky et al. (Eds.). Advances in Neural Computation, Machine Learning, and Cognitive Research V (NEUROINFORMATICS 2021). Studies in Computational Intelligence. Vol. 1008. Cham: Springer. 2022. PP. 276-284.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Surazhevsky I.A. at all. Noise-assisted persistence and recovery of memory state in amemristive spiking neuromorphic network.Chaos, Solitons and Fractals. 146 (2021). 110890.</mixed-citation><mixed-citation xml:lang="en">Surazhevsky I.A. at all. Noise-assisted persistence and recovery of memory state in amemristive spiking neuromorphic network.Chaos, Solitons and Fractals. 146 (2021). 110890.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Beskhlebnova G.A., Kotov V.B. The Variable Resistor Under a High-Frequency Signal. // B. Kryzhanovsky et al. (Eds.). Advances in Neural Computation, Machine Learning, and Cognitive Research VII (NEUROINFORMATICS 2023). Studies in Computational Intelligence. Vol. 1120. Springer Nature Switzerland AG. 2023. PP. 257–266. https://doi.org/10.1007/978-3-031-44865-2_28.</mixed-citation><mixed-citation xml:lang="en">Beskhlebnova G.A., Kotov V.B. The Variable Resistor Under a High-Frequency Signal. // B. Kryzhanovsky et al. (Eds.). Advances in Neural Computation, Machine Learning, and Cognitive Research VII (NEUROINFORMATICS 2023). Studies in Computational Intelligence. Vol. 1120. Springer Nature Switzerland AG. 2023. PP. 257–266. https://doi.org/10.1007/978-3-031-44865-2_28.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Kotov V.B., Beskhlebnova G.A. Use of High-Frequency Signals to Generate a Conductivity Matrix. // B. Kryzhanovsky et al. (Eds.). Advances in Neural Computation, Machine Learning, and Cognitive Research VIII (NEUROINFORMATICS 2024). Studies in Computational Intelligence. Vol. 1179. Springer Nature Switzerland AG. 2025. PP. 265-272.</mixed-citation><mixed-citation xml:lang="en">Kotov V.B., Beskhlebnova G.A. Use of High-Frequency Signals to Generate a Conductivity Matrix. // B. Kryzhanovsky et al. (Eds.). Advances in Neural Computation, Machine Learning, and Cognitive Research VIII (NEUROINFORMATICS 2024). Studies in Computational Intelligence. Vol. 1179. Springer Nature Switzerland AG. 2025. PP. 265-272.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Котов В.Б., Бесхлебнова Г.А. Поточечная запись информации в резисторную матрицу. // Труды НИИСИ РАН. Т. 14. №4. С. 33-40.</mixed-citation><mixed-citation xml:lang="en">Котов В.Б., Бесхлебнова Г.А. Поточечная запись информации в резисторную матрицу. // Труды НИИСИ РАН. Т. 14. №4. С. 33-40.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Kotov V.B., Yudkin F.A. Modeling and Characterization of Resistor Elements for Neuromorphic Systems. Optical Memory and Neural Networks (Information Optics). 2019, v.28, No.4, P. 271-282.</mixed-citation><mixed-citation xml:lang="en">Kotov V.B., Yudkin F.A. Modeling and Characterization of Resistor Elements for Neuromorphic Systems. Optical Memory and Neural Networks (Information Optics). 2019, v.28, No.4, P. 271-282.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">V.B. Kotov, Z. B. Sokhova. Two-frequency recording of information into a resistor array. // B. Kryzhanovsky et al. (Eds.). Advances in Neural Computation, Machine Learning, and Cognitive Research IX (NEUROINFORMATICS 2025). Studies in Computational Intelligence. Vol. 1241. Springer Nature Switzerland AG. 2026. PP. 463-476.</mixed-citation><mixed-citation xml:lang="en">V.B. Kotov, Z. B. Sokhova. Two-frequency recording of information into a resistor array. // B. Kryzhanovsky et al. (Eds.). Advances in Neural Computation, Machine Learning, and Cognitive Research IX (NEUROINFORMATICS 2025). Studies in Computational Intelligence. Vol. 1241. Springer Nature Switzerland AG. 2026. PP. 463-476.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
