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自相似分析
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  self-similarity analysis
     Abnormity Detection of Network Traffic Applied Self-Similarity Analysis of Network Traffics
     运用网络流量自相似分析的网络流量异常检测
短句来源
     Self-Similarity Analysis for Video Background Recognition
     采用自相似分析进行视频中的背景识别
短句来源
     Self-similarity analysis of network traffic (SSANT) includes aggregated variance, R/S analysis, periodic diagram and whittle methods.
     网络流量自相似分析有聚集方差法、R/S分析法、周期图法和Whittle法。
短句来源
  “自相似分析”译为未确定词的双语例句
     An Analytical Self-Similar Solution of the Mass Transfer Processes at Gas Bubbl-Water Interface
     气泡-水相界面上传质过程的自相似分析
短句来源
     A Self-affine fractality analysis was performed by using the experimental data of multiparticle production in pp collisions at 400GeV / c. Compared with the results obtained from the selfsimilar analysis, the self-affine fractality analysis shows a better scaling behavior within the limits of the experimenal resolution.
     利用400GeV/cpp碰撞多粒子产生的实验数据进行了自仿射分形分析,并与自相似分析相比较,结果表明在实验分辨能力范围内,自仿射分形分析具有嵔虾玫谋甓刃形
短句来源
     The normal model of network traffic was adopted in abnormity detection of network traffic based on SSANT. Self-Similarity Hurst parameter and time variable function H(t) of network traffics was analyzed.
     基于网络流量自相似分析的网络流量异常检测采用正常流量模型、对网络流量自相似性参数Hurst及其时变函数H(t)进行分析。
短句来源
     In this paper, we present a novel approach for background recognition using self-similarity.
     本文提出了一种对视频序列进行自相似分析,从而进行背景识别的方法。
短句来源
  相似匹配句对
     The Performance Analysis for Self-similar Traffic Flow
     相似业务流特性分析
短句来源
     Multifractal Analysis of Self-similar Traffic
     相似业务量的多重分形分析
短句来源
     Performance analysis of self-similar circumfluent network
     相似环流网状网性能分析
短句来源
     Statistical Multiplexing of Self-similar Traffic
     相似业务流复用特性分析
短句来源
     ANALYSIS OF THE CRITICAL MICRO-SCALE WITH SELF-SIMILARITY OF TURBULENT FLAME
     湍流火焰相似临界微尺度分析
短句来源
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  self-similarity analysis
This paper has introduced the method of self-similarity analysis of time series into the analysis and study of earthquake sequence, and then researched its application in earthquake prediction.
      
The results of self-similarity analysis were obtained for the earthquake sequences in North China, West South China, the Capital region of China, and for the East Yamashi region of Japan.
      
Self-similarity analysis reveals the existence of a high degree of self-organisation dominated by structures about 2.5 cm in size.
      


A Self-affine fractality analysis was performed by using the experimental data of multiparticle production in pp collisions at 400GeV / c. Compared with the results obtained from the selfsimilar analysis, the self-affine fractality analysis shows a better scaling behavior within the limits of the experimenal resolution.

利用400GeV/cpp碰撞多粒子产生的实验数据进行了自仿射分形分析,并与自相似分析相比较,结果表明在实验分辨能力范围内,自仿射分形分析具有嵔虾玫谋甓刃形

With the high development of computer network, the study of the network traffic is deeper. Now fractal theory is one of the most important methods in the research of the traffic. This paper introdees the applications of self- similar analysis method, the fractal interpolation method, the fractal prediction method and multifractal theory in the study of the traffic.

介绍了自相似分析方法、分形插值方法、分形预测方法和重分形分析方法在网络流量研究中的应用

Self-similarity analysis of network traffic (SSANT) includes aggregated variance, R/S analysis, periodic diagram and whittle methods. The normal model of network traffic was adopted in abnormity detection of network traffic based on SSANT. Self-Similarity Hurst parameter and time variable function H(t) of network traffics was analyzed. Network traffic was limited in real time and the abnormity characteristic was refined with database statistical analysis. Through detection of self-similarity change was measured,...

Self-similarity analysis of network traffic (SSANT) includes aggregated variance, R/S analysis, periodic diagram and whittle methods. The normal model of network traffic was adopted in abnormity detection of network traffic based on SSANT. Self-Similarity Hurst parameter and time variable function H(t) of network traffics was analyzed. Network traffic was limited in real time and the abnormity characteristic was refined with database statistical analysis. Through detection of self-similarity change was measured, then determine whether the current traffic is normal. Attack test of distributed decline service shows that abnormity detection of network traffic based on SSANT is more reliable on the recognition of network traffic abnormity than any other traditional method based on character recognition.

网络流量自相似分析有聚集方差法、R/S分析法、周期图法和Whittle法。基于网络流量自相似分析的网络流量异常检测采用正常流量模型、对网络流量自相似性参数Hurst及其时变函数H(t)进行分析。对网络流量进行实时限幅及使用数据库统计,通过检测自相似性变化,判断网络流量是否异常。分布式拒绝服务攻击试验表明,此法比传统的基于特征匹配的网络流量异常检测法在识别精度与实时性上有较大提高。

 
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