Title :
Intelligent methods for frame-based analysis of MPEG video models
Author_Institution :
Dept. of Commun. Technique & Technol., Univ. of Rousse, Bulgaria
Abstract :
In this study is presented using a neural networks and learning vector quantization (LVQ) for generating of histogram and a simple Markov chain models of GOP size sequence of MPEG video traffic. The implementation of both models is shown for frame-based analysis of the cell loss probability.
Keywords :
Markov processes; frame based representation; learning (artificial intelligence); neural nets; vector quantisation; video coding; GOP size sequence; LVQ; MPEG video traffic; Markov chain models; cell loss probability; frame-based analysis; histogram; learning vector quantization; neural networks; Artificial neural networks; Computational modeling; Delay; Histograms; Neural networks; Quality of service; Telecommunication traffic; Traffic control; Vector quantization; Video compression;
Conference_Titel :
Telecommunications in Modern Satellite, Cable and Broadcasting Service, 2003. TELSIKS 2003. 6th International Conference on
Print_ISBN :
0-7803-7963-2
DOI :
10.1109/TELSKS.2003.1246322
