A practical comparison of fBm estimators

摘要：

Wavelet estimator of the H parameter for fractional Brownian motion (fBm) is the most interesting one from a theoretical point of view. Indeed, Wavelet estimates are asymptotically efficient and has a complexity in only O(N). However, on limited time signals, the efficiency is not proved. In addition, some corrections have to be performed to maintain high performances. As a result, the complexity of the wavelet estimator increases so that other estimators can be thought of. In this paper, we are comparing wavelet estimator to maximum likelihood ones (classical and Whittle type) which both have also interesting theoretical properties. Results show that Whittle ML estimator is the best in terms of performances and complexity.

关键词： Fractal Estimators Maximum Likelihood wavelets

作者: G.Jacquet R.Harba A.Flores L.Vilcahuaman

作者单位: Télécom Saint-Etienne, Université Jean Monnet,42023 Saint-Etienne Cedex 2, France Institut Prisme, Polytech’Orléans - 12, rue de Blois,BP 6745, 45067 Orléans, France Pontificia Universidad Catolica del Peru, Facultad de Ciencias e Ingenieria, Lima, Peru

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 183-186

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）