Fast real-time Hurst parameter estimation via adaptive wavelet lifting

Dong Guo, Xiaodong Wang, Junshan Zhang

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)1266-1273
Number of pages8
JournalIEEE Transactions on Vehicular Technology
Volume53
Issue number4
DOIs
StatePublished - Jul 2004

Fingerprint

Hurst Parameter
Multiple access interference
Parameter estimation
Wavelet transforms
Code division multiple access
Lifting Scheme
Parameter Estimation
Computational complexity
Wavelets
Internet
Real-time
Multiple Access Interference
Vanishing Moments
Estimator
Internet Traffic
Dependent
Code Division multiple Access
Range of data
Wavelet Transform
Computational Complexity

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Networks and Communications

Cite this

Fast real-time Hurst parameter estimation via adaptive wavelet lifting. / Guo, Dong; Wang, Xiaodong; Zhang, Junshan.

In: IEEE Transactions on Vehicular Technology, Vol. 53, No. 4, 07.2004, p. 1266-1273.

Research output: Contribution to journalArticle

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