On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
Neural networks for admission control in an ATM network
selected papers from the Swedish conference on Connectionism in a broad perspective
Conference proceedings on Applications, technologies, architectures, and protocols for computer communications
Multiresolution learning paradigm and signal prediction
IEEE Transactions on Signal Processing
1997 Index IEEE Transactions On Signal Processing Vol. 45
IEEE Transactions on Signal Processing
Hi-index | 0.00 |
This work proposes a method of combining wavelet transforms to feed forward artificial neural networks for ATM (Asynchronous Transfer Mode) traffic prediction. Wavelet transforms are used to preprocess the nonlinear time- series in order to provide a step-closer phase learning paradigm to the artificial neural network. The network uses a variable length time window on approximation coefficients over all scales. It was observed that this approach could improve the generalization ability as well as the accuracy of the artificial neural network for ATM traffic prediction.