DocumentCode
698694
Title
IS PCA reliable for the analysis of fractional Brownian motion?
Author
Ozkurt, Tolga Esat ; Akgul, Tayfun
Author_Institution
Dept. of Comput. Sci., Istanbul Tech. Univ., Istanbul, Turkey
fYear
2005
fDate
4-8 Sept. 2005
Firstpage
1
Lastpage
4
Abstract
Estimation of the self-similarity parameter, also known as Hurst (H) parameter, is an important issue. In this paper, we study one of the H parameter estimation methods, namely the Principal Component Analysis (PCA) and show that this method may not give reliable results for the persistent part (H>0.5) of the fractional Brownian motion. Moreover, when the results are unreliable, the eigenvalue progression seriously deviates from linearity. Thus, with a linear-fit error threshold, one can comment on the reliability for the results of the PCA method.
Keywords
Brownian motion; eigenvalues and eigenfunctions; parameter estimation; principal component analysis; signal processing; H parameter estimation methods; Hurst parameter; PCA; eigenvalue progression; fractional Brownian motion; linear-fit error threshold; principal component analysis; self-similarity parameter estimation; Brownian motion; Correlation; Eigenvalues and eigenfunctions; Estimation; Principal component analysis; Reliability; Wind speed;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Conference, 2005 13th European
Conference_Location
Antalya
Print_ISBN
978-160-4238-21-1
Type
conf
Filename
7078287
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