| 基于EMD的自相似流量Hurst指数估计 |
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| 引用本文： | 单佩韦,李明.基于EMD的自相似流量Hurst指数估计[J].计算机工程,2008,34(23):128-129. |
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| 作者姓名： | 单佩韦 李明 |
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| 作者单位： | 华东师范大学信息科学与技术学院,上海,200062 |
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| 基金项目： | 国家自然科学基金资助项目 |
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| 摘 要： | 针对表征自相似网络流量统计特性的赫斯特(Hurst)指数，讨论一种基于经验模式分解的Hurst指数估计算法。该算法通过对自相似网络流量数据进行自适应分解，得到一组满足指定余项误差的固有模态函数分量，由其能量对数化函数与Hurst指数之间的线性拟合，估计出Hurst指数。实验表明，该算法能对自相似网络流量的Hurst指数进行自适应估计。
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| 关 键 词： | 自相似 赫斯特指数 经验模式分解 |
| 修稿时间： | |
Estimation of Hurst Index of Self-similar Traffic Based on EMD |
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| SHAN Pei-wei,LI Ming.Estimation of Hurst Index of Self-similar Traffic Based on EMD[J].Computer Engineering,2008,34(23):128-129. |
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| Authors: | SHAN Pei-wei LI Ming |
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| Affiliation: | (School of Information Science and Technology, East China Normal University, Shanghai 200062) |
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| Abstract: | This paper discusses a new method based on the Empirical Mode Decomposition(EMD) algorithm to estimate the Hurst index that is an important statistical parameter of self-similar network traffic. The algorithm can adaptively decompose self-similar traffic into a series of Intrinsic Mode Function(IMF). By using the relationship between the energy of IMFs and the Hurst index, it can adaptively estimate the Hurst parameter of self-similar traffic. Experimental results show that this algorithm can adaptively estimate the Hurst index of self-similar traffic. |
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| Keywords: | self-similar Hurst index Empirical Mode Decomposition(EMD) |
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