Journal article

Range Entropy: A Bridge between Signal Complexity and Self-Similarity

Amir Omidvarnia, Mostefa Mesbah, Mangor Pedersen, Graeme Jackson

ENTROPY | MDPI | Published : 2018

Abstract

Approximate entropy (ApEn) and sample entropy (SampEn) are widely used for temporal complexity analysis of real-world phenomena. However, their relationship with the Hurst exponent as a measure of self-similarity is not widely studied. Additionally, ApEn and SampEn are susceptible to signal amplitude changes. A common practice for addressing this issue is to correct their input signal amplitude by its standard deviation. In this study, we first show, using simulations, that ApEn and SampEn are related to the Hurst exponent in their tolerance r and embedding dimension m parameters. We then propose a modification to ApEn and SampEn called range entropy or RangeEn. We show that RangeEn is more ..

View full abstract

Grants

Awarded by National Health and Medical Research Council (NHMRC) of Australia


Awarded by NHMRC practitioner fellowship


Awarded by Melbourne Bioinformatics at the University of Melbourne


Funding Acknowledgements

This work was supported by the National Health and Medical Research Council (NHMRC) of Australia (program grant 1091593). G.J. was supported by an NHMRC practitioner fellowship (1060312). The Florey Institute of Neuroscience and Mental Health acknowledges the strong support from the Victorian Government and in particular the funding from the Operational Infrastructure Support Grant. This research was supported by Melbourne Bioinformatics at the University of Melbourne, grant number UOM0042.