Fast Sample Entropy - saenkd(dim ,r ,sig )
It implements a fast computation of Sample Entropy solving the equivalent orthogonal range search method using the k-d tree for the search of neighbors as proposed in literature by Yu-Hsiang Pan et al., 2011.
for detailed explanation of the algorithm look for:
- "COMPUTING MULTISCALE ENTROPY WITH ORTHOGONAL RANGE SEARCH"
- "Fast computation of sample entropy and approximate entropy in biomedicine"
this code may be used also for the computation of multiscale sample entropy, just provide to this code the coarse-grained time series.
Detalis are in the help section of the file saenkd.m
Cite As
Filippo (2024). Fast Sample Entropy - saenkd(dim ,r ,sig ) (https://www.mathworks.com/matlabcentral/fileexchange/48574-fast-sample-entropy-saenkd-dim-r-sig), MATLAB Central File Exchange. Retrieved .
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- AI, Data Science, and Statistics > Statistics and Machine Learning Toolbox > Cluster Analysis and Anomaly Detection > Nearest Neighbors >
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