An application of RBF neural network in video traffic modeling and predicting
Si Xiong, Atm R · Journal of China Institute of Communications · 2000
One of the key technologies of ATM is traffic control Whether a traffic control solution is effective depending on the through understanding of the characteristics and the ability of prediction The traditional analytical methods are obviously intractable for video traffic As a settlement,a radial basis function(RBF)neural networks has been adopted in this paper for video traffic modeling and prediction In addition,a proposal concerning the LBG basis algorithm and Hestenes singular value decomposition(SVD)method are involved,to be able to improve the selection of the centers of hidden layer neuron and the calculation method of the weights of the output layer synapse in the RBF network A series of practical video data has been used to evaluate the proposed approach