n-Order and maximum fuzzy similarity entropy for discrimination of signals of different complexity: Application to fetal heart rate signals
Solving the problem of setting entropy descriptors by varying the pattern size instead of the tolerance. Improving the discrimination of signals of different complexity such as fBm and fetal heart rate signal (normal-IUGR). Linking intrinsic features of time series with the optimal pattern size that maximizes the similarity entropy. Improving the discrimination by developing a new paradigm as the n-order fuzzy similarity entropy.
n-order fuzzy entropy complexity fetal heart rate maximum similarity fetal distress