Effect of Noise on Moving Cut Data-Permutation Entropy
WEN-XIANG LUO, Li Wan, SI-MIN LAI · DEStech Transactions on Engineering and Technology Research · 2018
The effect of peak noise and white Gaussian noise on moving cut data-permutation entropy method is discussed by constructing the nonlinear ideal time series. The results show that the moving cut data-permutation entropy method can accurately detect the location of the mutational point, even if the time series with high noise level, which showed that the effect of peak noise and white Gaussian noise on the result of this method is small. The moving cut data-permutation entropy has strong anti-noise ability, which is beneficial to the application of this method in actual observation data.