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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">bsuir</journal-id><journal-title-group><journal-title xml:lang="ru">Доклады БГУИР</journal-title><trans-title-group xml:lang="en"><trans-title>Doklady BGUIR</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1729-7648</issn><issn pub-type="epub">2708-0382</issn><publisher><publisher-name>БГУИР</publisher-name></publisher></journal-meta><article-meta><article-id custom-type="elpub" pub-id-type="custom">bsuir-400</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>Статьи</subject></subj-group></article-categories><title-group><article-title>ПАРАМЕТРИЧЕСКИЙ АУДИОКОДЕР НА ОСНОВЕ РАЗРЕЖЕННОЙ АППРОКСИМАЦИИ С ПЕРЦЕПТУАЛЬНО-ОПТИМИЗИРОВАННЫМ СЛОВАРЕМ ЧАСТОТНО-ВРЕМЕННЫХ ФУНКЦИЙ</article-title><trans-title-group xml:lang="en"><trans-title>PARAMETRIC AUDIO CODER BASED ON SPARSE APPROXIMATION WITH FRAME-BASED PSYCHOACOUSTIC OPTIMIZED WAVELET PACKET DICTIONARY</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>Петровский</surname><given-names>Ал. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Petrovsky</surname><given-names>Al. A.</given-names></name></name-alternatives><email xlink:type="simple">noemail@neicon.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>Герасимович</surname><given-names>В. Ю.</given-names></name><name name-style="western" xml:lang="en"><surname>Herasimovich</surname><given-names>V. Y.</given-names></name></name-alternatives><email xlink:type="simple">noemail@neicon.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff xml:lang="ru" id="aff-1"><institution>Белорусский государственный университет информатики и радиоэлектроники</institution><country>Belarus</country></aff><pub-date pub-type="collection"><year>2015</year></pub-date><pub-date pub-type="epub"><day>03</day><month>06</month><year>2019</year></pub-date><volume>0</volume><issue>1</issue><fpage>5</fpage><lpage>11</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Петровский А.А., Герасимович В.Ю., 2019</copyright-statement><copyright-year>2019</copyright-year><copyright-holder xml:lang="ru">Петровский А.А., Герасимович В.Ю.</copyright-holder><copyright-holder xml:lang="en">Petrovsky A.A., Herasimovich V.Y.</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://doklady.bsuir.by/jour/article/view/400">https://doklady.bsuir.by/jour/article/view/400</self-uri><abstract><p>Рассматривается метод частотно-временного преобразования сигналов, показывается преимущества совместного, частотно-временного анализа перед традиционным раздельным анализом во временной, либо частотной областях. Дается описание алгоритма согласованной подгонки для декомпозиции сигнала в базис частотно-временных функций, а также модификация данного алгоритма с использованием принципов психоакустики для выбора наиболее важных для восприятия компонент аудиосигнала. Предлагается схема построения универсального аудиокодера на основе разреженной аппроксимации с перцептуально-оптимизированным словарем вейвлет коэффициентов.</p></abstract><trans-abstract xml:lang="en"><p>Time-frequency signal transform is considered. Advantages of joint time-frequency analysis over traditional separate analysis in time or frequency domains are shown. Matching pursuit algorithm and modified psychoacoustic matching pursuit describes. Universal audiocoder scheme based on sparse approximation with frame-based psychoacoustic optimized wavelet packet dictionary proposed.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>частотно-временные преобразования</kwd><kwd>пакет дискретного вейвлет преобразования</kwd><kwd>согласованная подгонка</kwd><kwd>психоакустическая модель</kwd><kwd>аудиокодер</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">Painter T., Spanias A. // Proceedings of the IEEE. 2000. Vol. 88, № 4. P. 451-513.</mixed-citation><mixed-citation xml:lang="en">Painter T., Spanias A. // Proceedings of the IEEE. 2000. Vol. 88, № 4. P. 451-513.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Mallat S.G., Zhang Z. // IEEE Transactions on signal processing. 1993. Vol. 41, № 12. 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