Dynamic Hurst Parameter Estimation of Multi-fractional Processes in Impulse Noise Environment. Issue 1 (February 2020) - Zhao, Shuyuan; Sheng, Hu; Qiu, Tianshuang
Abstract: 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.