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Using Linear Prediction to Mitigate End Effects in Empirical Mode Decomposition

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Citation Author(s):
Steven Sandoval, Matthew Bredin, and Phillip L.~De Leon
Submitted by:
Matthew Bredin
Last updated:
26 November 2018 - 4:23pm
Document Type:
Poster
Document Year:
2018
Event:
Presenters Name:
Matthew Bredin

Abstract 

Abstract: 

It is well known that empirical mode decomposition can suffer from computational instabilities at the signal boundaries. These ``end effects'' cause two problems: 1) sifting termination issues, i.e.~convergence and 2) estimation error, i.e.~accuracy. In this paper, we propose to use linear prediction in conjunction with a previous method to address end effects, to further mitigate these problems. We compare the proposed mitigation to the existing method and provide simulations which demonstrate that the new approach improves intrinsic mode function estimation accuracy while significantly improving convergence.

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GlobalSIP_2018_Poster___Mitigating_End_Effects.pdf

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