Analysis of the synergistic complementarity between bubble entropy and dispersion entropy in the application of feature extraction - Jiang, Xinru; Yi, Yingmin; Wu, Junxian (Frontiers in Physics, 2023)
Most of the existing studies on the improvement of entropy are based on the theory of single entropy, but ignore the relationship between one entropy and another. Inspired by the synergistic relationship between bubble entropy and permutation entropy, which has been pointed out by previous authors, this paper aims to explore the relationship between bubble entropy and dispersion entropy. Since dispersion entropy outperforms permutation entropy in many aspects, it provides better stability and enhances the computational efficiency of permutation entropy, we speculate that there should be potential synergy between dispersion entropy and bubble entropy as well. Through experiments, we demonstrated the synergistic complementarity between BE and DE, and proposed a double features extraction method based on BE and DE. For single feature extraction experiment, dispersion entropy and bubble entropy have better recognition performance for sea state signals and bearing signals respectively; in double feature extraction, the combination of bubble entropy and dispersion entropy makes the recognition rate of sea state signals increase by 10.5% and the recognition rate of bearing signals reach 99.5%.