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		<identifier>oai:zbc.uz.zgora.pl:85939</identifier>
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<dc:title xml:lang="pl"><![CDATA[An algorithm for arbitrary-order cumulant tensor calculation in a sliding window of data streams]]></dc:title>
<dc:creator><![CDATA[Domino, Krzysztof]]></dc:creator>
<dc:creator><![CDATA[Gawron, Piotr]]></dc:creator>
<dc:subject xml:lang="pl"><![CDATA[high order cumulants]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[time-series statistics]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[non-normally distributed data]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[data streaming]]></dc:subject>
<dc:description xml:lang="pl"><![CDATA[High-order cumulant tensors carry information about statistics of non-normally distributed multivariate data. In this work we present a new efficient algorithm for calculation of cumulants of arbitrary orders in a sliding window for data streams. We show that this algorithm offers substantial speedups of cumulant updates compared with the current solutions. The proposed algorithm can be used for processing on-line high-frequency multivariate data and can find applications, e.g., in on-line signal filtering and classification of data streams.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[To present an application of this algorithm, we propose an estimator of non-Gaussianity of a data stream based on the norms of high order cumulant tensors. We show how to detect the transition from Gaussian distributed data to non-Gaussian ones in a data stream. In order to achieve high implementation efficiency of operations on super-symmetric tensors, such as cumulant tensors, we employ a block structure to store and calculate only one hyper-pyramid part of such tensors.]]></dc:description>
<dc:publisher><![CDATA[Zielona Góra: Uniwersytet Zielonogórski]]></dc:publisher>
<dc:contributor><![CDATA[Gamper, Johann - ed.]]></dc:contributor>
<dc:contributor><![CDATA[Wrembel, Robert - ed.]]></dc:contributor>
<dc:date><![CDATA[2019]]></dc:date>
<dc:type xml:lang="pl"><![CDATA[artykuł]]></dc:type>
<dc:identifier><![CDATA[http://www.zbc.uz.zgora.pl/repozytorium/Content/85939/AMCS_2019_29_1_15.pdf]]></dc:identifier>
<dc:identifier><![CDATA[https://zbc.uz.zgora.pl/repozytorium/dlibra/publication/100951/edition/85939/content]]></dc:identifier>
<dc:identifier><![CDATA[oai:zbc.uz.zgora.pl:85939]]></dc:identifier>
<dc:source xml:lang="pl"><![CDATA[AMCS, volume 29, number 1 (2019)]]></dc:source>
<dc:source xml:lang="pl"><![CDATA[https://www.amcs.uz.zgora.pl/?action=papers&issue=111]]></dc:source>
<dc:language><![CDATA[eng]]></dc:language>
<dc:relation><![CDATA[oai:zbc.uz.zgora.pl:publication:100951]]></dc:relation>
<dc:rights xml:lang="pl"><![CDATA[Biblioteka Uniwersytetu Zielonogórskiego]]></dc:rights>
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