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Proceedings Paper

Transient signal detection using the empirical mode decomposition
Author(s): Michael L. Larsen; Jeffrey Ridgway; Cye H. Waldman; Michael Gabbay; Rodney R. Buntzen; Brad Battista
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Paper Abstract

In this paper, we report on efforts to develop signal processing methods appropriate for the detection of man-made electromagnetic signals in the nonlinear and nonstationary underwater electromagnetic noise environment of the littoral. Using recent advances in time series analysis methods [Huang et al., 1998], we present new techniques for detection and compare their effectiveness with conventional signal processing methods, using experimental data from recent field experiments. These techniques are based on an empirical mode decomposition which is used to isolate signals to be detected from noise without a priori assumptions. The decomposition generates a physically motivated basis for the data.

Paper Details

Date Published: 26 October 2004
PDF: 16 pages
Proc. SPIE 5559, Advanced Signal Processing Algorithms, Architectures, and Implementations XIV, (26 October 2004); doi: 10.1117/12.561301
Show Author Affiliations
Michael L. Larsen, Information Systems Labs., Inc. (United States)
Jeffrey Ridgway, Information Systems Labs., Inc. (United States)
Cye H. Waldman, Information Systems Labs., Inc. (United States)
Michael Gabbay, Information Systems Labs., Inc. (United States)
Rodney R. Buntzen, Information Systems Labs., Inc. (United States)
Brad Battista, Information Systems Labs., Inc. (United States)


Published in SPIE Proceedings Vol. 5559:
Advanced Signal Processing Algorithms, Architectures, and Implementations XIV
Franklin T. Luk, Editor(s)

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