Title :
A New Congestion Control Algorithm Based on RBFNN
Author :
Weifeng, Shan ; Baohong, Meng ; Wei, Zhu
Author_Institution :
Commun. & Command Acad. of PLA, Wuhan
Abstract :
This paper presents a new sequential learning algorithm for radial basis function neural network (RBFNN) based on local projection named local projection network (LPN). Earlier studies have shown that RBFNN is well suited for online adaptive control of nonlinear time varying systems as it adjust its size by adding and pruning the hidden neurons based on the input data. Simulation results indicate that RBF with the new algorithm controller performs better in reducing the congestion episodes and maintaining the desirable QoS.
Keywords :
asynchronous transfer mode; learning systems; neural nets; neurocontrollers; quality of service; radial basis function networks; telecommunication congestion control; asynchronous transfer mode; congestion control algorithm; local projection network; quality of service; radial basis function neural network; sequential learning algorithm; Asynchronous transfer mode; Bit rate; Clustering algorithms; Communication system control; Communication system traffic control; Feeds; Hilbert space; Information technology; Neural networks; Programmable logic arrays; ATM; Congestion Control; RBFNN;
Conference_Titel :
Information Technology: New Generations, 2008. ITNG 2008. Fifth International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
0-7695-3099-0
DOI :
10.1109/ITNG.2008.21
