Estimating Hurst exponent with wavelet packet

Applied in many areas, from original hydrology to modern computer networking, Hurst exponent provides us with an indicator that the analyzed data is a completely random process or has underlying trends. But a good estimation of Hurst exponent remains complicated as R/S algorithm shows. Recurring to fractal mathematics, especially the research on fractal Brownian motion (fBm), wavelet packet transform is introduced to estimate Hurst exponent. Compared with wavelet transform and other estimating methods, the wavelet packet algorithm is found able to provide more accurate result. And another advantage of wavelet packet is the extensive choice of available analyzing wavelet filter functions