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dc.contributor.authorBaxevani, Anastassiaen
dc.contributor.authorPodgórski, K.en
dc.creatorBaxevani, Anastassiaen
dc.creatorPodgórski, K.en
dc.date.accessioned2019-12-02T10:33:49Z
dc.date.available2019-12-02T10:33:49Z
dc.date.issued2009
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/56475
dc.description.abstractThe Lamperti transformation of a self-similar process is a stationary process. In particular, the fractional Brownian motion transforms to the second order stationary Gaussian process. This process is represented as a series of independent processes. The terms of this series are Ornstein-Uhlenbeck processes if H1/2. From the representation effective approximations of the process are derived. The corresponding results for the fractional Brownian motion are obtained by applying the inverse Lamperti transformation. Implications for simulating the fractional Brownian motion are discussed.en
dc.sourceActa Physica Polonica Ben
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-67649126584&partnerID=40&md5=bcbe9dc6e355e8e90351e8416ef4b21c
dc.subjectMathematical transformationsen
dc.subjectBrownian movementen
dc.subjectFractional Brownian motionen
dc.subjectLinear combinationsen
dc.subjectStationary processen
dc.subjectMarkovianen
dc.subjectSecond ordersen
dc.subjectOrnstein-Uhlenbeck processen
dc.subjectSelf-similar processen
dc.subjectStationary Gaussian processen
dc.subjectTwo-dimensional structuresen
dc.titleSeries decomposition of fractional Brownian motion and its Lamperti transformen
dc.typeinfo:eu-repo/semantics/article
dc.description.volume40
dc.description.issue5
dc.description.startingpage1395
dc.description.endingpage1435
dc.author.facultyΣχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Μαθηματικών και Στατιστικής / Department of Mathematics and Statistics
dc.type.uhtypeArticleen
dc.description.notes<p>Cited By :2</p>en
dc.source.abbreviationActa Phys Pol Ben
dc.contributor.orcidBaxevani, Anastassia [0000-0002-7498-9048]


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