ON WAVELET-BASED METHODS FOR HURST INDEX ESTIMATION OF SELF-SIMILAR TRAFFIC
自相似数据流的Hurst指数小波求解法分析

Existing wavelet methods for the estimation of the Hurst parameter of self-similar traffic are systematically analyzed and examined. The effects of wavelet functions, vanishing moments and wavelet decomposition levels on the results of wavelet methods for acquiring the Hurst index are investigated via numerical experiments. Some useful conclusions are drawn on the relationship between the accuracy of the methods and the selection of the order of vanishing moments and the selection of wavelet functions.