Modeling MPEG-4 VBR video traffic by using ANFIS. (English) Zbl 1202.94030
Huang, De-Shuang (ed.) et al., Intelligent computing in signal processing and pattern recognition. International conference on intelligent computing, ICIC 2006, Kunming, China, August 16–19, 2006. Berlin: Springer (ISBN 3-540-37257-1/pbk). Lecture Notes in Control and Information Sciences 345, 958-963 (2006).
Summary: Video traffic predicting and modeling are very important for compressed video transmission. The traditional method delineates the process by a rigid model with several parameters, which are difficult to estimate. In this paper, the MPEG-4 VBR (Variable Bit Rate) video traffic is modeled by the ANFIS (Adaptive Neuro-Fuzzy Inference System). Then, it is applied to modeling and predicting the MPEG-4 VBR video traffic. Simulations show the GoP (Group of Pictures) loss probabilities in actual video traffic are very close to those in ANFIS modeling traffic at the same experimental conditions and the prediction errors (1/SNR) are very small.
For the entire collection see [Zbl 1103.94002].
For the entire collection see [Zbl 1103.94002].
MSC:
| 94A08 | Image processing (compression, reconstruction, etc.) in information and communication theory |
