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Activity Number:
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565
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Type:
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Contributed
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Date/Time:
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Thursday, August 6, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Physical and Engineering Sciences
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| Abstract - #304391 |
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Title:
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A Robust Nonlinear Method for Spectral Analysis
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Author(s):
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Ta-Hsin Li*+
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Companies:
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IBM T. J. Watson Research Center
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Address:
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, , ,
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Keywords:
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Time series ; spectral analysis ; robustness ; least absolute deviation
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Abstract:
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A new type of periodogram is obtained by replacing the least-squares criterion with an Lp-norm criterion in the regression formulation of the ordinary periodogram. A relationship is established between the new periodogram and the serial dependence of a random process. It is shown that the new periodogram can strike a balance between the robustness against heavy-tailed noise and the effectiveness like the ordinary periodogram under normal conditions. Simulation results and real-data examples are provided to demonstrate the performance of the new periodogram for spectral analysis and signal detection.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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