Discrete-Time Models for Statistically Self-Similar Signals.
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| Title: | Discrete-Time Models for Statistically Self-Similar Signals. |
|---|---|
| Authors: | Seungsin Lee, Wei Zhao, Narasimha, Rajesh, Rao, Raghuveer M. |
| Source: | IEEE Transactions on Signal Processing. May2003, Vol. 51 Issue 5, p1221. 10p. 4 Black and White Photographs, 1 Diagram, 14 Graphs. |
| Subjects: | Signal processing, Discrete-time systems, Scaling laws (Statistical physics) |
| Abstract: | Wide-sense statistical self-similarity in continuous-time random processes is defined through invariance of its first-order and second-order statistics to scaling in time. Since scaling has an unambiguous definition in continuous-time but not in discrete-time, researchers have provided various definitions of discrete-time self-similarity without reference to scaling. This paper proposes a discrete-time continuous-dilation scaling operator and develops a framework based on it for formulating statistical self-similarity from first principles in a manner analogous to the continuous-time development. Relationship between the resulting model and fractional order transfer function systems is presented. The potential for using this model in applications involving long-range dependent phenomena is explored. [ABSTRACT FROM AUTHOR] |
| Copyright of IEEE Transactions on Signal Processing is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 9618239 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Discrete-Time Models for Statistically Self-Similar Signals. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Seungsin+Lee%22">Seungsin Lee</searchLink><br /><searchLink fieldCode="AR" term="%22Wei+Zhao%22">Wei Zhao</searchLink><br /><searchLink fieldCode="AR" term="%22Narasimha%2C+Rajesh%22">Narasimha, Rajesh</searchLink><br /><searchLink fieldCode="AR" term="%22Rao%2C+Raghuveer+M%2E%22">Rao, Raghuveer M.</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IEEE+Transactions+on+Signal+Processing%22">IEEE Transactions on Signal Processing</searchLink>. May2003, Vol. 51 Issue 5, p1221. 10p. 4 Black and White Photographs, 1 Diagram, 14 Graphs. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Signal+processing%22">Signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Discrete-time+systems%22">Discrete-time systems</searchLink><br /><searchLink fieldCode="DE" term="%22Scaling+laws+%28Statistical+physics%29%22">Scaling laws (Statistical physics)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Wide-sense statistical self-similarity in continuous-time random processes is defined through invariance of its first-order and second-order statistics to scaling in time. Since scaling has an unambiguous definition in continuous-time but not in discrete-time, researchers have provided various definitions of discrete-time self-similarity without reference to scaling. This paper proposes a discrete-time continuous-dilation scaling operator and develops a framework based on it for formulating statistical self-similarity from first principles in a manner analogous to the continuous-time development. Relationship between the resulting model and fractional order transfer function systems is presented. The potential for using this model in applications involving long-range dependent phenomena is explored. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IEEE Transactions on Signal Processing is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=9618239 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1109/TSP.2003.810281 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 1221 Subjects: – SubjectFull: Signal processing Type: general – SubjectFull: Discrete-time systems Type: general – SubjectFull: Scaling laws (Statistical physics) Type: general Titles: – TitleFull: Discrete-Time Models for Statistically Self-Similar Signals. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Seungsin Lee – PersonEntity: Name: NameFull: Wei Zhao – PersonEntity: Name: NameFull: Narasimha, Rajesh – PersonEntity: Name: NameFull: Rao, Raghuveer M. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2003 Type: published Y: 2003 Identifiers: – Type: issn-print Value: 1053587X Numbering: – Type: volume Value: 51 – Type: issue Value: 5 Titles: – TitleFull: IEEE Transactions on Signal Processing Type: main |
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