@inproceedings{4bc6a93dcf2e4d8cba0373d28c878f96,
title = "A novel gaussian window approach for empirical mode decomposition",
abstract = "Empirical mode decomposition (EMD) is an algorithmic construction for decomposing multi-component signals into a series of intrinsic mode functions (IMFs). However, traditional EMD may encounter the difficulty of mode mixing when a signal contains intermittency. To solve the difficulty, a Gaussian window averaging method is proposed to construct the mean envelope of a given signal in each sifting process. The numerical analysis also demonstrates promising reliability with the proposed algorithm.",
keywords = "Empirical mode decomposition, Gaussian, Intrinsic mode function, Mode mixing",
author = "Wu, {Shuen De} and Wu, {Chiu Wen} and Liu, {Cha Lin} and Huang, {Yan Hao} and Lee, {Kung Yen}",
year = "2012",
doi = "10.4028/www.scientific.net/AMR.457-458.274",
language = "English",
isbn = "9783037853559",
series = "Advanced Materials Research",
pages = "274--277",
booktitle = "Advanced Materials and Engineering Materials",
note = "2011 International Conference on Advanced Materials and Engineering Materials, ICAMEM2011 ; Conference date: 22-11-2011 Through 24-11-2011",
}