Abstract Details
Activity Number:
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391
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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Korean International Statistical Society
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Abstract #311381
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View Presentation
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Title:
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Quantile-Based EMD and Its Application
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Author(s):
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Minsu Park*+ and Hee-Seok Oh and Donghoh Kim
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Companies:
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Seoul National University and Seoul National University and Sejong University
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Keywords:
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Empirical mode decomposition ;
Quantile smoothing splines ;
Mean envelope ;
Intrinsic mode functions
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Abstract:
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The main goal of this study is to propose a new approach of empirical mode decomposition (EMD) that analyzes noisy signals efficiently. The conventional EMD has been widely used to decompose nonlinear and nonstationary signals into some components according the intrinsic frequency called intrinsic mode functions (IMFs). However, IMFs obtained by EMD are sensitive to noises or outliers due to interpolation step in construction of envelopes; hence, EMD may not be efficient in decomposing noisy signals. This paper presents a new EMD that analyzes noisy signals as well as is robust to outliers with holding the merits of EMD. The key ingredient of the proposed method is to apply the quantile smoothing to a noisy signal itself instead of interpolating local extrema when constructing mean envelope. The contribution of the proposed EMD is two-fold: (1) it efficiently decomposes various types of noisy signal, and (2) it provides the fast implementation algorithm bypassing the identification of local extrema. It is demonstrated that the proposed method can produce substantially effective results for both one-dimensional signal and two-dimensional image through simulation studies.
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Authors who are presenting talks have a * after their name.
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