TY - JOUR
T1 - Fast real-time Hurst parameter estimation via adaptive wavelet lifting
AU - Guo, Dong
AU - Wang, Xiaodong
AU - Zhang, Junshan
N1 - Funding Information:
Manuscript received February 19, 2003; revised December 22, 2003 and March 6, 2004. This work was supported in part by the U.S. National Science Foundation (NSF) under Grant DMS-0225692 and Grant CCR-0225826 and in part by the U.S. Office of Naval Research (ONR) unde r Grant N00014-03-1-0039.
PY - 2004/7
Y1 - 2004/7
N2 - A new real-time estimator of the Hurst parameter of a long-range dependent process is developed based on the lifting scheme for wavelet transform. Compared with the existing wavelet-based estimator, the new method performs inplace computation and reduces the computational complexity by about half. We also propose a median-based nonlinear lifting scheme to mitigate the border effects and the noise in the data, by adaptively adjusting the number of vanishing moments of the wavelet. The proposed algorithms are applied to estimate the Hurst parameters in two types of long-range dependent processes, namely, the multiple-access interference in a code-division multiple-access packet data network, and the measurement data of Internet traffic.
AB - A new real-time estimator of the Hurst parameter of a long-range dependent process is developed based on the lifting scheme for wavelet transform. Compared with the existing wavelet-based estimator, the new method performs inplace computation and reduces the computational complexity by about half. We also propose a median-based nonlinear lifting scheme to mitigate the border effects and the noise in the data, by adaptively adjusting the number of vanishing moments of the wavelet. The proposed algorithms are applied to estimate the Hurst parameters in two types of long-range dependent processes, namely, the multiple-access interference in a code-division multiple-access packet data network, and the measurement data of Internet traffic.
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U2 - 10.1109/TVT.2004.830146
DO - 10.1109/TVT.2004.830146
M3 - Article
AN - SCOPUS:3943075860
SN - 0018-9545
VL - 53
SP - 1266
EP - 1273
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 4
ER -