Kesirli brown deviniminde hurst parametresi kestirim yöntemlerinin karşilaştirmasi

Süleymam Baykut*, Melike Erol, Tolga Esat Özkurt, Tayfum Akgül

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

Özet

Most natural processes show self-similarity. Self-similarity or 1/f behavior has been a popular concept to describe the scale invariance of time-series. Fractional Brownian motion (fBm) is one of the most preferred models of 1/f processes since statistical behavior of fBm is determined by a single (Hurst) parameter, H. Consequently, estimation of H has been an important issue and several methods are developed to estimate H. It has been a complicated issue to determine which one of the estimators yields more robust estimates. In this work, we compare the performance of three methods, namely, Higuchi, Wavelet Based and recently proposed Principal Component Analysis methods. We apply these estimators to data sets with varying H values. We also analyze the effect of data length on the robustness of the estimators. Finally, we investigate the effects of periodicity interfering with fBm which is a common case encountered in practice.

Tercüme edilen katkı başlığıA comparative study on the estimation of hurst parameter of fractional brownian motion
Orijinal dilTürkçe
Ana bilgisayar yayını başlığıProceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005
Sayfalar672-675
Sayfa sayısı4
DOI'lar
Yayın durumuYayınlandı - 2005
EtkinlikIEEE 13th Signal Processing and Communications Applications Conference, SIU 2005 - Kayseri, Turkey
Süre: 16 May 200518 May 2005

Yayın serisi

AdıProceedings of the IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005
Hacim2005

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???IEEE 13th Signal Processing and Communications Applications Conference, SIU 2005
Ülke/BölgeTurkey
ŞehirKayseri
Periyot16/05/0518/05/05

Parmak izi

Kesirli brown deviniminde hurst parametresi kestirim yöntemlerinin karşilaştirmasi' araştırma başlıklarına git. Birlikte benzersiz bir parmak izi oluştururlar.

Alıntı Yap