Open AccessDynamic Hurst Parameter Estimation of Multi-fractional Processes in Impulse Noise Environment
Author(s) -
Shuyuan Zhao,
Hu Sheng,
Tianshuang Qiu
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/750/1/012005
Subject(s) - hurst exponent , rescaled range , estimation theory , impulse (physics) , detrended fluctuation analysis , impulse response , computer science , noise (video) , mathematics , algorithm , statistics , artificial intelligence , mathematical analysis , physics , geometry , quantum mechanics , scaling , image (mathematics)
Hurst parameter estimation is the key issue for long range dependent system modeling and data prediction. Dynamic Hurst parameter estimation of data with impulse noise is difficult. In this research, the Dynamic Hurst parameter of multi-fractional signal is estimated using sliding windowed R/S method and generalized Hurst exponent. Simulation results show that sliding windowed R/S method and generalized Hurst exponent can effectively analyze the Hurst parameter of impulse noise contaminated signals.