Title :
New training pattern selection method for ATM call admission neural control
Author :
Jurado, Alejandro ; Sandoval, F.
fDate :
3/31/1994 12:00:00 AM
Abstract :
A new training pattern selection method for adaptive neural control using backpropagation learning is presented. When applying this method to an asynchronous transfer mode (ATM) call admission control, some advantages are observed: a very small training pattern table is sufficient, the learning is independent of observed data, and the controller is easily adaptable to traffic changes. The proposed neural control model is analysed by computer simulations in heterogeneous traffic environments and the results show its effectiveness compared with other methods
Keywords :
asynchronous transfer mode; backpropagation; telecommunication traffic; ATM call admission neural control; adaptive neural control; asynchronous transfer mode; backpropagation learning; computer simulations; controller; heterogeneous traffic environments; learning; neural control model; observed data; traffic changes; training pattern selection method; training pattern table;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:19940371
