Analysis of Moments Based Methods for Fractional Gaussian Noise Estimation

Fractional Gaussian noise, given as the increment of fractional Brownian motion, is a stationary Gaussian process characterized by the Hurst parameter. In the paper, moments based estimators of the Hurst parameter are presented and analyzed with respect to asymptotic variance.

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Bibliographic Details
Published in:IEEE transactions on signal processing 2012-07, Vol.60 (7), p.3823-3827
Main Author: Mossberg, M.
Format: Article
Language:English
Subjects:
Applied sciences
Asymptotic properties
Asymptotic variance
Brownian motion
covariance function
Detection, estimation, filtering, equalization, prediction
Estimation
Estimators
Exact sciences and technology
fractional Gaussian noise
Gaussian
Gaussian noise
Gaussian processes
Information, signal and communications theory
Matematik
Materials
Mathematics
Minimization
Moment methods
Noise
parameter estimation
Signal and communications theory
Signal processing
Signal, noise
Statistics
Statistik
Telecommunications and information theory
Transaction processing
Variance
Vectors
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Description
Summary:Fractional Gaussian noise, given as the increment of fractional Brownian motion, is a stationary Gaussian process characterized by the Hurst parameter. In the paper, moments based estimators of the Hurst parameter are presented and analyzed with respect to asymptotic variance.
ISSN:1053-587X
1941-0476
1941-0476
DOI:10.1109/TSP.2012.2191545