@inproceedings{8b60656dae85454682c1cf6d5ea0515a,
title = "Gaussian kernel approximate entropy algorithm for analyzing irregularity of time-series",
abstract = "Approximate entropy (ApEn) has been widely used to analyze the complexity of time series. However, the inconsistency that ApEn exhibits not only limits its applications but also raises questions about its validity. Addressing this issue, this paper presents a novel Gaussian kernel approximate entropy (GApEn) algorithm. The experimental results demonstrate that GApEn performs better than ApEn in terms of relative consistency, stability and statistical accuracy.",
keywords = "Approximate entropy, Gaussian kernel, Relative consistency",
author = "Xu, \{L. I.Sheng\} and Wang, \{Kuan Quan\} and Wang, \{L. U.\}",
year = "2005",
doi = "10.1109/ICMLC.2005.1527935",
language = "英语",
isbn = "078039092X",
series = "2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005",
publisher = "IEEE Computer Society",
pages = "5605--5608",
booktitle = "2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005",
address = "美国",
note = "International Conference on Machine Learning and Cybernetics, ICMLC 2005 ; Conference date: 18-08-2005 Through 21-08-2005",
}