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<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.0 20120330//EN" "JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article"><front><journal-meta><journal-id journal-id-type="publisher-id">INFORMATICA</journal-id><journal-title-group><journal-title>Informatica</journal-title></journal-title-group><issn pub-type="epub">0868-4952</issn><issn pub-type="ppub">0868-4952</issn><publisher><publisher-name>VU</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">inf14207</article-id><article-id pub-id-type="doi">10.15388/Informatica.2003.016</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research article</subject></subj-group></article-categories><title-group><article-title>Optimal Estimation of the Parameters of Linear Periodically Time‐varying Systems</article-title></title-group><contrib-group><contrib contrib-type="Author"><name><surname>Kazlauskas</surname><given-names>Kazys</given-names></name><email xlink:href="mailto:kazlausk@ktl.mii.lt">kazlausk@ktl.mii.lt</email><xref ref-type="aff" rid="j_INFORMATICA_aff_000"/></contrib><aff id="j_INFORMATICA_aff_000">Institute of Mathematics and Informatics, Vilnius Pedagogical University, Akademijos 4, LT‐2021 Vilnius, Lithuania</aff></contrib-group><pub-date pub-type="epub"><day>01</day><month>01</month><year>2003</year></pub-date><volume>14</volume><issue>2</issue><fpage>213</fpage><lpage>222</lpage><history><date date-type="received"><day>01</day><month>01</month><year>2003</year></date></history><abstract><p>This paper discusses the linear periodically time‐varying (LPTV) system parameter estimation using a block approach. An block algorithm is proposed for optimal estimation of the parameters of LPTV system from the input sequence and the output sequence corrupted by additive Gaussianly distributed noise. In the proposed method, the least squares error criterion has been used.The algorithm provides a useful computational tool based on an appropriate theoretical foundation for parameter estimation of linear time‐invariant (LTI) systems from input and output data. Simulation results are presented that demonstrate the performance of the approach.</p></abstract><kwd-group><label>Keywords</label><kwd>parameter estimation</kwd><kwd>least squares</kwd><kwd>block approach</kwd><kwd>linear periodically time‐varying systems</kwd><kwd>numerical simulation</kwd></kwd-group></article-meta></front></article>