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Proceedings Paper

Parameter estimation of locally stationary wavelet processes
Author(s): Arthur Johnson; Ching-Chung Li
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Paper Abstract

This paper considers the extraction of information from a locally stationary process modelled by wavelet packets. A method is presented to select subprocesses that characterize the key aspects of the nonstationary process for pattern analysis. The estimated parameters of the selected subprocesses are used to infer the process' time varying behavior. The estimated parameters can be used as features in the attempt to distinguish changing states within a process or differentiate two different locally stationary processes.

Paper Details

Date Published: 13 November 2003
PDF: 10 pages
Proc. SPIE 5207, Wavelets: Applications in Signal and Image Processing X, (13 November 2003); doi: 10.1117/12.505549
Show Author Affiliations
Arthur Johnson, Univ. of Pittsburgh (United States)
Ching-Chung Li, Univ. of Pittsburgh (United States)


Published in SPIE Proceedings Vol. 5207:
Wavelets: Applications in Signal and Image Processing X
Michael A. Unser; Akram Aldroubi; Andrew F. Laine, Editor(s)

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