Fast computation of approximate entropy

Authors:
George Manis
Affiliations:
University of Ioannina, Department of Computer Science, P.O. Box 1186, Ioannina 45110, Greece
Venue:
Computer Methods and Programs in Biomedicine
Year:
2008

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Abstract

The approximate entropy (ApEn) is a measure of systems complexity. The implementation of the method is computationally expensive and requires execution time analogous to the square of the size of the input signal. We propose here a fast algorithm which speeds up the computation of approximate entropy by detecting early some vectors that are not similar and by excluding them from the similarity test. Experimental analysis with various biomedical signals revealed a significant improvement in execution times.