A new entropy measure based on the Renyi entropy rate using Gaussian kernels

Woodcock, D. and Nabney, Ian T. (2006). A new entropy measure based on the Renyi entropy rate using Gaussian kernels. Technical Report. Aston University, Birmingham.

Abstract

The concept of entropy rate is well defined in dynamical systems theory but is impossible to apply it directly to finite real world data sets. With this in mind, Pincus developed Approximate Entropy (ApEn), which uses ideas from Eckmann and Ruelle to create a regularity measure based on entropy rate that can be used to determine the influence of chaotic behaviour in a real world signal. However, this measure was found not to be robust and so an improved formulation known as the Sample Entropy (SampEn) was created by Richman and Moorman to address these issues. We have developed a new, related, regularity measure which is not based on the theory provided by Eckmann and Ruelle and proves a more well-behaved measure of complexity than the previous measures whilst still retaining a low computational cost.

Divisions: Engineering & Applied Sciences > Computer science
Engineering & Applied Sciences > Computer science research group
Engineering & Applied Sciences > Systems analytics research institute (SARI)
Uncontrolled Keywords: approximate entropy,ApEn,entropy rate,dynamical systems theory,sample entropy,SampEn
Published Date: 2006-02-24
Authors: Woodcock, D.
Nabney, Ian T. ( 0000-0003-1513-993X)

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