DocumentCode :
1188095
Title :
PCA Based Hurst Exponent Estimator for fBm Signals Under Disturbances
Author :
Li, Li ; Hu, Jianming ; Chen, Yudong ; Zhang, Yi
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing
Volume :
57
Issue :
7
fYear :
2009
fDate :
7/1/2009 12:00:00 AM
Firstpage :
2840
Lastpage :
2846
Abstract :
In this paper, the validity of PCA eigenspectrum based Hurst exponent estimator proposed in[J. B. Gao, Y. Cao, and J.-M. Lee, ldquoPrincipal Component Analysis of 1/f alpha noise,rdquo Phys. Lett. A, vol. 314, no. 5-6, pp. 392-400, 2003] for single fBm signal is proved. Moreover, how to apply this estimator for fBm signals corrupted with some other signals are discussed. Theoretical analysis and experiments show that it can also be used for 1) mixed fBm signals with different Hurst exponents, 2) fBm signals corrupted with additive Gaussian white noise when the signal-to-noise ratio (SNR) is not too small, and 3) fBm signals corrupted with additive deterministic sine/cosine signals. However, the estimation accuracy depends on the SNR value for the first two situations.
Keywords :
1/f noise; AWGN; Brownian motion; eigenvalues and eigenfunctions; principal component analysis; spectral analysis; 1/falpha noise; Hurst exponent estimator; PCA eigenspectrum; SNR; additive Gaussian white noise; additive deterministic cosine signal; additive deterministic sine signal; fractional Brownian motion signal; signal-to-noise ratio; Fractal Brownian motion (fBm); Hurst exponent; principal component analysis (PCA);
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2009.2016877
Filename :
4799115
Link To Document :
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