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2000
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Non Linear Traffic Modeling of VBR MPEG-2 Video Sources

8 years 10 months ago
Non Linear Traffic Modeling of VBR MPEG-2 Video Sources
In this paper, a neural network scheme is presented for modeling VBR MPEG-2 video sources. In particular, three non linear autoregressive models (NAR) are proposed to model the aggregate MPEG-2 video sequence, each of which corresponds to one of the three types of frames (I, P and B frames). Then, the optimal mean-squared error predictor of the NAR model is implemented using a feedforward neural network with a tapped delay line (TDL) filter. A novel algorithm is also introduced, which handles the significant effect of the correlation among the I, P and B frames on the estimation of network resources. Furthermore, a new mechanism is proposed to improve the modeling accuracy, especially at high bit rates, based on a generalized regression neural network. Experimental studies and computer simulations illustrate the efficiency and robustness of the proposed model as predictor of the network resources compared to conventional models.
Anastasios D. Doulamis, Nikolaos D. Doulamis, Stef
Added 31 Jul 2010
Updated 31 Jul 2010
Type Conference
Year 2000
Where ICMCS
Authors Anastasios D. Doulamis, Nikolaos D. Doulamis, Stefanos D. Kollias
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