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] |
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| Database: | Engineering Source |
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