JSM 2014 Home
Online Program Home
My Program

Abstract Details

Activity Number: 391
Type: Contributed
Date/Time: Tuesday, August 5, 2014 : 2:00 PM to 3:50 PM
Sponsor: Korean International Statistical Society
Abstract #311381 View Presentation
Title: Quantile-Based EMD and Its Application
Author(s): Minsu Park*+ and Hee-Seok Oh and Donghoh Kim
Companies: Seoul National University and Seoul National University and Sejong University
Keywords: Empirical mode decomposition ; Quantile smoothing splines ; Mean envelope ; Intrinsic mode functions
Abstract:

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.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2014 program




2014 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Professional Development program, please contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.