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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/12434

Title: A GACS modeling approach for MPEG broadcast video
Authors: Alheraish, A.
Alshebeili, S.A.
Alamri, T.
Keywords: Auto-regressive (AR); Communication networks; MPEG video; Nonlinear system; Video broadcast; Video modeling
Issue Date: 2004
Publisher: IEEE
Citation: IEEE Transactions on Broadcasting Volume 50, Issue 2, June 2004, Pages 132-141
Abstract: Accurate MPEG source models are needed to support high speed networks such as ATM and Internet. In this paper, we propose a video model called Gaussian Auto-regressive and Chi-Square processes (GACS) for MPEG coded video traffic. The GACS models the sizes of MPEG I, P, and B frames according to the MPEG syntax I -frame < P - frame < B - frame. This is done by decomposing the process of each frame size into a weighted sum of a number of chi-square sequences. Each chi-square sequence is then obtained by squaring a Gaussian process, which is efficiently generated by using an Auto-regressive (AR) model whose parameters are determined from an estimated covariance matrix. We evaluate the effectiveness of our model by conducting a series of experiments using a wide variety of long empirical video sequences. The results show that the proposed model leads to excellent data fit and accurate prediction of queuing performance
URI: http://hdl.handle.net/123456789/12434
ISSN: 00189316
Appears in Collections:College of Engineering

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