| Paper: | SPTM-P6.10 | ||
| Session: | Non-stationary Signals and Time-Frequency Analysis | ||
| Time: | Wednesday, May 17, 16:30 - 18:30 | ||
| Presentation: | Poster | ||
| Topic: | Signal Processing Theory and Methods: Non-stationary Signals and Time-Frequency Analysis | ||
| Title: | PRINCIPAL COMPONENT ANALYSIS OF THE FRACTIONAL BROWNIAN MOTION FOR 0 < H < 0.5 | ||
| Authors: | Tolga Esat Ozkurt, University of Pittsburgh, United States; Tayfun Akgul, Suleyman Baykut, Istanbul Technical University, Turkey | ||
| Abstract: | Principal component analysis (PCA) has been proposed for the estimation of the self-similarity parameter H, namely the Hurst parameter of 1/f processes, and an analytical proof is provided only for H=0.5 in a recent study [1]. In our paper, we extend this study by deriving explicit expressions and presenting an analytical proof for the range of 0 < H < 0.5 (the anti-persistent part of the fractional Brownian motion). We also show via simulations that the accuracy of the estimated H values may decrease considerably as the theoretical H value increases towards the persistent part (0.5 < H < 1). | ||
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