教授 博士生导师 硕士生导师
性别: 男
毕业院校: 大连理工大学
学位: 博士
所在单位: 生物医学工程学院
学科: 信号与信息处理. 生物医学工程
办公地点: 大连理工大学创新园大厦
联系方式: 电子邮箱:qiutsh@dlut.edu.cn; 电话:15898159801
电子邮箱: qiutsh@dlut.edu.cn
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论文类型: 期刊论文
发表时间: 2011-04-01
发表刊物: IET SIGNAL PROCESSING
收录刊物: Scopus、SCIE、EI
卷号: 5
期号: 2
页面范围: 209-225
ISSN号: 1751-9675
摘要: The presence and the nature of long-range dependent (LRD) are usually characterised by the Hurst parameter. In order to meet the requirements of analysing the LRD processes, a number of practical estimation methods have been proposed in the literature. Furthermore, some efforts have been made to evaluate the accuracy and validity of the Hurst estimators for LRD processes. In practice, however, many signals measured are corrupted with various types of noises, and sometimes even the concerned signal itself has infinite variance. In such cases, which estimator has the best robustness to the LRD property of the signal and its noise involved, and how robust it is are still unresolved. The aim of this paper is to make a quantitative analysis of the robustness of twelve commonly used Hurst parameter estimators. In this paper, we considered four types of LRD signals with possible noises. They are 1) LRD process alone; 2) LRD process corrupted by 30 dB signal to noise ratio (SNR) white Gaussian noise; 3) LRD process corrupted by 30 dB SNR stable noise; 4) fractional autoregressive moving average (FARIMA) time series with stable innovations. Moreover, the standard errors of each estimator are provided.