Modified multiscale entropy for short-term time series analysis
Journal
Physica A: Statistical Mechanics and its Applications
Journal Volume
392
Journal Issue
23
Pages
5865-5873
Date Issued
2013
Author(s)
Abstract
Multiscale entropy (MSE) is a prevalent algorithm used to measure the complexity of a time series. Because the coarse-graining procedure reduces the length of a time series, the conventional MSE algorithm applied to a short-term time series may yield an imprecise estimation of entropy or induce undefined entropy. To overcome this obstacle, the modified multiscale entropy (MMSE) was developed. The coarse-graining procedure was replaced with a moving-average procedure and a time delay was incorporated for constructing template vectors in calculating sample entropy. For conducting short-term time series analysis, this study shows that the MMSE algorithm is more reliable than the conventional MSE. © 2013 Elsevier B.V. All rights reserved.
Type
journal article