2003Unpublished venueRequires access

Improved autoregressive model

C. Amo-Quarm, M. Mezhoudi, Kaliappa Ravindran

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Abstract

The autoregressive process has been used by several authors to model MPEG video traffic and attempts to capture the frame correlation as well as the Gaussian shape of the bit rate variation. However, the autoregressive process alone does not capture scene changes. In this paper, we propose an autoregressive model of order P, AR(P) + IAP (interrupted autoregressive process), to capture scene changes. We compare the model performance to that of the actual video trace, as well as the autoregressive process without scene changes.

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What this paper is about

The autoregressive process has been used by several authors to model MPEG video traffic and attempts to capture the frame correlation as well as the Gaussian shape of the bit rate variation. However, the autoregressive process alone does not capture scene changes. In this paper, we propose an autoregressive model of order P, AR(P) + IAP (interrupted autoregressive process), to capture scene changes. We compare the model performance to that of the actual video trace, as well as the autoregressive process without scene changes.

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Available abstract

The autoregressive process has been used by several authors to model MPEG video traffic and attempts to capture the frame correlation as well as the Gaussian shape of the bit rate variation. However, the autoregressive process alone does not capture scene changes. In this paper, we propose an autoregressive model of order P, AR(P) + IAP (interrupted autoregressive process), to capture scene changes. We compare the model performance to that of the actual video trace, as well as the autoregressive process without scene changes.

Key concepts: Autoregressive model, STAR model, Computer science, Nonlinear autoregressive exogenous model, Gaussian process, Autoregressive integrated moving average, Process (computing), Frame (networking)

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