{"id":7323,"date":"2021-04-19T09:40:50","date_gmt":"2021-04-19T06:40:50","guid":{"rendered":"http:\/\/journals.khnu.km.ua\/vestnik\/?p=7323"},"modified":"2021-08-05T15:10:55","modified_gmt":"2021-08-05T12:10:55","slug":"%d0%bc%d0%b5%d1%82%d0%be%d0%b4-%d0%bf%d1%96%d0%b4%d0%b2%d0%b8%d1%89%d0%b5%d0%bd%d0%bd%d1%8f-%d0%bf%d1%80%d0%be%d0%b4%d1%83%d0%ba%d1%82%d0%b8%d0%b2%d0%bd%d0%be%d1%81%d1%82%d1%96-%d1%81%d0%bf%d0%b5","status":"publish","type":"post","link":"https:\/\/journals.khnu.km.ua\/vestnik\/?p=7323","title":{"rendered":"\u041c\u0435\u0442\u043e\u0434 \u043f\u0456\u0434\u0432\u0438\u0449\u0435\u043d\u043d\u044f \u043f\u0440\u043e\u0434\u0443\u043a\u0442\u0438\u0432\u043d\u043e\u0441\u0442\u0456 \u0441\u043f\u0435\u043a\u0442\u0440\u0430\u043b\u044c\u043d\u043e\u0433\u043e \u043e\u0446\u0456\u043d\u044e\u0432\u0430\u043d\u043d\u044f \u0432\u0438\u043f\u0430\u0434\u043a\u043e\u0432\u0438\u0445 \u0441\u0438\u0433\u043d\u0430\u043b\u0456\u0432"},"content":{"rendered":"<p><!--more--><\/p>\n<p style=\"text-align: center;\">\u041c\u0415\u0422\u041e\u0414 \u041f\u0406\u0414\u0412\u0418\u0429\u0415\u041d\u041d\u042f \u041f\u0420\u041e\u0414\u0423\u041a\u0422\u0418\u0412\u041d\u041e\u0421\u0422\u0406 \u00a0\u0421\u041f\u0415\u041a\u0422\u0420\u0410\u041b\u042c\u041d\u041e\u0413\u041e \u041e\u0426\u0406\u041d\u042e\u0412\u0410\u041d\u041d\u042f \u0412\u0418\u041f\u0410\u0414\u041a\u041e\u0412\u0418\u0425 \u0421\u0418\u0413\u041d\u0410\u041b\u0406\u0412<\/p>\n<p style=\"text-align: center;\">METHOD OF INCREASING THE PRODUCTIVITY OF SPECTRAL EVALUATION OF RANDOM SIGNALS<\/p>\n<p><strong>\u0421\u0442\u043e\u0440\u0456\u043d\u043a\u0438: 145-150. \u041d\u043e\u043c\u0435\u0440: \u21161, 2021 (293)<\/strong> <a href=\"http:\/\/journals.khnu.km.ua\/vestnik\/wp-content\/uploads\/2021\/08\/24-1.pdf\"> <img loading=\"lazy\" class=\"size-full wp-image-69 alignnone\" src=\"http:\/\/journals.khnu.km.ua\/vestnik\/wp-content\/uploads\/2021\/01\/pdf.png\" alt=\"\" width=\"76\" height=\"32\" \/><\/a><br \/>\n<strong>\u0410\u0432\u0442\u043e\u0440\u0438:<\/strong><br \/>\n\u0413.\u0413. \u0411\u041e\u0420\u0422\u041d\u0418\u041a, \u041c.\u0412. \u0412\u0410\u0421\u0418\u041b\u042c\u041a\u0406\u0412\u0421\u042c\u041a\u0418\u0419, \u0421.\u041e. \u041a\u0418\u0420\u0418\u041b\u042e\u041a<br \/>\n\u0412\u0456\u043d\u043d\u0438\u0446\u044c\u043a\u0438\u0439 \u043d\u0430\u0446\u0456\u043e\u043d\u0430\u043b\u044c\u043d\u0438\u0439 \u0442\u0435\u0445\u043d\u0456\u0447\u043d\u0438\u0439 \u0443\u043d\u0456\u0432\u0435\u0440\u0441\u0438\u0442\u0435\u0442<br \/>\nG.G. BORTNYK, M.V. VASYLKIVSKYI, S.O. KYRYLYUK<br \/>\nVinnytsia National Technical University<br \/>\n<strong>DOI:<\/strong> <a href=\"https:\/\/www.doi.org\/10.31891\/2307-5732-2021-293-1-145-150\">https:\/\/www.doi.org\/10.31891\/2307-5732-2021-293-1-145-150<\/a><br \/>\n<strong>\u0420\u0435\u0446\u0435\u043d\u0437\u0456\u044f\/Peer review :<\/strong> 19.01.2021 \u0440.<br \/>\n<strong>\u041d\u0430\u0434\u0440\u0443\u043a\u043e\u0432\u0430\u043d\u0430\/Printed :<\/strong> 10.03.2021 \u0440.<\/p>\n<p style=\"text-align: center;\"><strong>\u0410\u043d\u043e\u0442\u0430\u0446\u0456\u044f \u043c\u043e\u0432\u043e\u044e \u043e\u0440\u0438\u0433\u0456\u043d\u0430\u043b\u0443<\/strong><\/p>\n<p>\u0423 \u0440\u043e\u0431\u043e\u0442\u0456 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u043e \u0432\u0438\u0441\u043e\u043a\u043e\u043f\u0440\u043e\u0434\u0443\u043a\u0442\u0438\u0432\u043d\u0438\u0439 \u043c\u0435\u0442\u043e\u0434 \u0441\u043f\u0435\u043a\u0442\u0440\u0430\u043b\u044c\u043d\u043e\u0433\u043e \u043e\u0446\u0456\u043d\u044e\u0432\u0430\u043d\u043d\u044f \u0432\u0438\u043f\u0430\u0434\u043a\u043e\u0432\u0438\u0445 \u0441\u0438\u0433\u043d\u0430\u043b\u0456\u0432, \u044f\u043a\u0438\u0439 \u0431\u0430\u0437\u0443\u0454\u0442\u044c\u0441\u044f \u043d\u0430 \u043f\u0440\u043e\u0446\u0435\u0434\u0443\u0440\u0456 \u043a\u043e\u043c\u0431\u0456\u043d\u043e\u0432\u0430\u043d\u043e\u0433\u043e \u043e\u0431\u0440\u043e\u0431\u043b\u0435\u043d\u043d\u044f \u043d\u0435\u043f\u0435\u0440\u0435\u043a\u0440\u0438\u0432\u043d\u0438\u0445 \u043f\u0456\u0434\u043f\u043e\u0441\u043b\u0456\u0434\u043e\u0432\u043d\u043e\u0441\u0442\u0435\u0439 \u0432\u0438\u0431\u043e\u0440\u043e\u043a \u0441\u0438\u0433\u043d\u0430\u043b\u0443 \u0443 \u0447\u0430\u0441\u043e\u0432\u0456\u0439 \u0456 \u0447\u0430\u0441\u0442\u043e\u0442\u043d\u0456\u0439 \u043e\u0431\u043b\u0430\u0441\u0442\u0456.<br \/>\n\u0410\u043d\u0430\u043b\u0456\u0437 \u0435\u0444\u0435\u043a\u0442\u0438\u0432\u043d\u043e\u0441\u0442\u0456 \u0437\u0430\u043f\u0440\u043e\u043f\u043e\u043d\u043e\u0432\u0430\u043d\u043e\u0433\u043e \u043c\u0435\u0442\u043e\u0434\u0443 \u043f\u0456\u0434\u0442\u0432\u0435\u0440\u0434\u0438\u0432, \u0449\u043e \u0437\u0430\u0432\u0434\u044f\u043a\u0438 \u0440\u043e\u0437\u0440\u043e\u0431\u043b\u0435\u043d\u0456\u0439 \u043f\u0440\u043e\u0446\u0435\u0434\u0443\u0440\u0456 \u0446\u0438\u0444\u0440\u043e\u0432\u043e\u0433\u043e \u043e\u0431\u0440\u043e\u0431\u043b\u0435\u043d\u043d\u044f \u0441\u0438\u0433\u043d\u0430\u043b\u0456\u0432 \u0432\u0434\u0430\u0454\u0442\u044c\u0441\u044f \u043f\u0456\u0434\u0432\u0438\u0449\u0438\u0442\u0438 \u043f\u0440\u043e\u0434\u0443\u043a\u0442\u0438\u0432\u043d\u0456\u0441\u0442\u044c \u0441\u043f\u0435\u043a\u0442\u0440\u0430\u043b\u044c\u043d\u043e\u0433\u043e \u043e\u0446\u0456\u043d\u044e\u0432\u0430\u043d\u043d\u044f \u0441\u0438\u0433\u043d\u0430\u043b\u0456\u0432 \u0443 2,0\u00f79,0 \u0440\u0430\u0437\u0456\u0432 \u0437\u0430\u043b\u0435\u0436\u043d\u043e \u0432\u0456\u0434 \u043e\u0431\u2019\u0454\u043c\u0443 \u0430\u043d\u0430\u043b\u0456\u0437\u043e\u0432\u0430\u043d\u043e\u0457 \u0432\u0438\u0431\u0456\u0440\u043a\u0438 \u0441\u0438\u0433\u043d\u0430\u043b\u0443 \u0442\u0430 \u0447\u0438\u0441\u043b\u0430 \u043e\u0431\u0440\u043e\u0431\u043b\u044e\u0432\u0430\u043d\u0438\u0445 \u043f\u0456\u0434\u043f\u043e\u0441\u043b\u0456\u0434\u043e\u0432\u043d\u043e\u0441\u0442\u0435\u0439. \u041c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u0438\u0439 \u0432\u0438\u0433\u0440\u0430\u0448 \u0443 \u043f\u0440\u043e\u0434\u0443\u043a\u0442\u0438\u0432\u043d\u043e\u0441\u0442\u0456 \u0434\u043e\u0441\u044f\u0433\u0430\u0454\u0442\u044c\u0441\u044f \u0437\u0430 \u0443\u043c\u043e\u0432\u0438, \u043a\u043e\u043b\u0438 \u043f\u043e\u0447\u0430\u0442\u043a\u043e\u0432\u0438\u0439 \u043c\u0430\u0441\u0438\u0432 \u0434\u0430\u043d\u0438\u0445 \u0440\u043e\u0437\u0431\u0438\u0432\u0430\u0454\u0442\u044c\u0441\u044f \u043d\u0430 64 \u043f\u0456\u0434\u043f\u043e\u0441\u043b\u0456\u0434\u043e\u0432\u043d\u043e\u0441\u0442\u0456.<br \/>\n<strong>\u041a\u043b\u044e\u0447\u043e\u0432\u0456 \u0441\u043b\u043e\u0432\u0430:<\/strong> \u0441\u043f\u0435\u043a\u0442\u0440\u0430\u043b\u044c\u043d\u0430 \u0433\u0443\u0441\u0442\u0438\u043d\u0430 \u043f\u043e\u0442\u0443\u0436\u043d\u043e\u0441\u0442\u0456, \u0448\u0432\u0438\u0434\u043a\u0435 \u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0435\u043d\u043d\u044f \u0424\u0443\u0440\u2019\u0454, \u0432\u0438\u043f\u0430\u0434\u043a\u043e\u0432\u0456 \u0441\u0438\u0433\u043d\u0430\u043b\u0438, \u043f\u0440\u043e\u0434\u0443\u043a\u0442\u0438\u0432\u043d\u0456\u0441\u0442\u044c.<\/p>\n<p style=\"text-align: center;\"><strong>\u0420\u043e\u0437\u0448\u0438\u0440\u0435\u043d\u0430 \u0430\u043d\u043e\u0442\u0430\u0446\u0456\u044f \u0430\u043d\u0433\u043b\u0456\u0439\u0441\u044c\u043a\u043e\u044e \u043c\u043e\u0432\u043e\u044e<\/strong><\/p>\n<p>The paper presents a high-performance method of spectral estimation of random signals, which is based on the procedure of combined processing of non-overlapping subsequences of signal samples in the time and frequency domain.<br \/>\nIt is shown that the traditional method of spectral estimation of signals requires powerful computing tools that are able to perform fast Fourier transform (FFT) according to the classical algorithm with high speed. But the implementation of this approach limits the frequency range of the analyzed signals. The high demands placed primarily on the performance of the means of spectral evaluation of random signals, encourage developers to reconsider traditional methods of using FFT. Despite the results obtained in these methods, the issue of improving the performance of digital spectral evaluation of random signals in real time remains relevant.<br \/>\nThe aim of the work is to increase the productivity of spectral evaluation of random signals by reducing the number of operations in the implementation of all stages of digital signal processing.<br \/>\nThe paper proposes an approach that combines the features of periodogram and correlogram estimation methods. The array of input data is divided into non-overlapping subsequences of samples in each. To determine the sample power spectrum, the FFT algorithm in a given frequency band is used. The proposed method is based on the use of a rectangular weight window. To reduce the variance of the estimate, it is necessary to carry out further processing using a correlation window. As a result, we obtain a weighted correlation estimate. At the last stage, the FFT of the correlation function is performed, which makes it possible to obtain the final expression for estimating the signal power spectrum.<br \/>\nThe analysis of the efficiency of the proposed method confirmed that thanks to the developed method it is possible to increase the productivity of digital spectral evaluation of signals by 2.0 \u00f7 9.0 times depending on the volume of the analyzed signal sample and the number of processed subsequences. The maximum performance gain is achieved when the initial data set is divided into 64 subsequences.<br \/>\nThe proposed method can be used in radio and telecommunication systems for spectral evaluation of random signals in real time.<br \/>\n<strong>Keywords:<\/strong> power spectral density, fast Fourier transform, random signals, productivity.<\/p>\n<p style=\"text-align: center;\"><strong>References<\/strong><\/p>\n<ol>\n<li>Bendat Dzh. Prikladnoj analiz sluchajnykh dannykh \/ Dzh. Bendat, A. Pirsol ; per. s angl. \u2013 M. : Mir, 1989. \u2013 540 s. \u2013 ISBN 5-03-001071-8.<\/li>\n<li>Bortnyk H.H. Merezhi abonentskoho dostupu : navchalnyi posibnyk \/ H.H. Bortnyk, V.M. Kychak, O.V. Stalchenko, Yablonskyi V.F. \u2013 Vinnytsia : UNIVERSUM-Vinnytsia, 2009. \u2013 201 s.<\/li>\n<li>Bortnyk H.H. Systemy peredavannia v elektrozviazku : navchalnyi posibnyk \/ H.H. Bortnyk, O.A. Semeniuk, O.V. Stalchenko. \u2013 Vinnytsia : VNTU, 2006. \u2013 138 s.<\/li>\n<li>Bortnyk H.H. Metody ta zasoby pervynnoho tsyfrovoho obroblennia radiosyhnaliv \/ H. Bortnyk, M.V. Vasylkivskyi, V.M.Kychak. \u2013 Vinnytsia : VNTU, 2016. \u2013 168 s.<\/li>\n<li>Marpl-ml. S.L. Cifrovoj spektral&#8217;nyj analiz i ego prilozheniya \/ S.L. Marpl-ml. ; per. s angl. \u2013 M. : Mir, 1990. \u2013 584 s. \u2013 ISBN 5-03-001191-9.<\/li>\n<li>Bortnyk H.H. Metod otsiniuvannia determinovanykh skladovykh fazovoho dryzhannia u tsyfrovykh systemakh peredavannia \/ H.H. Bortnyk, M.V. Vasylkivskyi, O.H. Bortnyk \/\/ Vymiriuvalna ta obchysliuvalna tekhnika v tekhnolohichnykh protsesakh. \u2013 2012. \u2013 \u2116 3. \u2013 S. 45-48.<\/li>\n<li>Bortnyk H.H. Metody ta zasoby pidvyshchennia efektyvnosti otsiniuvannia fazovoho dryzhannia syhnaliv u telekomunikatsiinykh systemakh : monohrafiia \/ H.H. Bortnyk, M.V. Vasylkivskyi, V.M. Kychak. \u2013 Vinnytsia : VNTU, 2015. &#8211; 140 s.<\/li>\n<li>Ajficher EH. Cifrovaya obrabotka signalov \/ EH. Ajficher, Dzhervis ; per. s angl. \u2013 M. : Vil&#8217;yams, 2004. \u2013 992 s.<\/li>\n<li>Bortnyk H.H. Metody ta prystroi otsiniuvannia kharakterystyk impulsno-kodovykh moduliatoriv shyrokosmuhovykh syhnaliv : monohrafiia \/ H.H. Bortnyk, V.M. Kychak, N.O. Punchenko. \u2013 Vinnytsia : VNTU, 2014. \u2013 147 s.<\/li>\n<li>Bortnyk H.H. Metod tsyfrovoho spektralnoho analizu vuzkosmuhovykh syhnaliv \/ H.H. Bortnyk, O.H. Bortnyk, O.V. Stalchenko \/\/ Visnyk Vinnytskoho politekhnichnoho instytutu. \u2013 2016. \u2013 \u2116 4. \u2013 S. 97-101.<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"_links":{"self":[{"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/posts\/7323"}],"collection":[{"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=7323"}],"version-history":[{"count":3,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/posts\/7323\/revisions"}],"predecessor-version":[{"id":7536,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/posts\/7323\/revisions\/7536"}],"wp:attachment":[{"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=7323"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=7323"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=7323"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}