We propose refined composite multivariate multiscale fuzzy entropy (RCmvMFE).
The coarse-graining step of RCmvMFE uses variance (RCmvMFEcdef27912" title="Click to view the MathML source">σ2) or mean (RCmvMFEμ).
The introduced fuzzy membership function significantly decreases the running time.
Our simulations demonstrate that RCmvMFEcdef27912" title="Click to view the MathML source">σ2 and RCmvMFEμ lead to more stable results.
RCmvMFEcdef27912" title="Click to view the MathML source">σ2 and RCmvMFEμ are less sensitive to the length of signals.