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Wavelet-Based Estimation of Long-Range Dependence in MPEG Video Traces

机译:基于小波的MPEG视频迹线的远程依赖性估算

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Correct and efficient estimation of the Hurst parameter of long-range dependent (LRD) video traces is important in traffic analysis. The low computational cost and the wavelets' scale invariance make the wavelet transform suitable for analysis of LRD processes. In this paper, we apply wavelet-based estimation of the Hurst parameter to MPEG-1 and MPEG-4 encoded video sequences. Frequency-domain estimators (periodogram and wavelet-based) produce different Hurst parameters compared to time-domain estimators (R/S and variance-time plot). Wavelet-based estimators often produce Hurst parameters that are dose to or greater than one. Our analysis indicates that possible causes for the unreliable performance of the wavelet-based estimators are the non-stationarity of the scaling exponent and the existence of both short-range and long-range dependent components in the video traces.
机译:对远程依赖(LRD)视频迹线的赫斯特参数的正确有效估计在流量分析中很重要。低计算成本和小波尺寸不变性使小波变换适用于分析LRD流程。在本文中,我们将基于小波的估计应用于MPEG-1和MPEG-4编码的视频序列。与时域估计器(R / S和方差时绘图)相比,频域估计器(基于周期图和小波和小波的)产生不同的训练参数。基于小波的估计经常会产生剂量或大于1的肿仓参数。我们的分析表明,基于小波的估计器的不可靠性性能的可能原因是缩放指数的非实用性,以及视频迹线中的短程和远程相关组件的存在。

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