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本文提出了一种新的ＶＢＲ视频业务模型：三态马尔科夫链下的双一阶自回归Ｇａｍｍａ序列（２ＧＡＲ（１））．该模型的Ｇａｍｍａ分布特性能较好地描述ＶＢＲ业务比特流的分布，由自相关函数决定的模型系数更充分地描述了自相关函数的行为，利用三态马尔科夫链的两个补充过程可以较理想地描述场景切换下的视频业务模型．文中对这一模型进行了较详细的分析，给出了确定模型参数的方法，并得出了一些重要结论．
In this paper, we present a new VBR video service model: the bi-order autoregressive Gamma sequence (2-GAR (1)) under a tri-state Markov chain. The Gamma distribution of this model can describe the distribution of VBR service bitstream better. The model coefficients determined by autocorrelation function can describe the behavior of autocorrelation function more fully. The two complementary processes of three-state Markov chain can be It is more descriptive of the video traffic model under scene switching. In this paper, a more detailed analysis of this model, given the method to determine the model parameters, and reached some important conclusions.