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26 October 2004 Transient signal detection using the empirical mode decomposition
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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.
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Michael L. Larsen, Jeffrey Ridgway, Cye H. Waldman, Michael Gabbay, Rodney R. Buntzen, and Brad Battista "Transient signal detection using the empirical mode decomposition", Proc. SPIE 5559, Advanced Signal Processing Algorithms, Architectures, and Implementations XIV, (26 October 2004); https://doi.org/10.1117/12.561301
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