Growing and pruning (GAP) RBF networks for call admission control in ATM traffic management
This thesis presents a study on the use of recently developed neural networks MRAN (Minimal Resource Allocation Network) and GAP (Growing and Pruning neural network) for the performance enhancement of Call Admission Control in Asynchronous Transfer Mode (ATM) networks. GAP and MRAN generate a minima...
Saved in:
Main Author: | Mohit Aiyar |
---|---|
Other Authors: | Narasimhan Sundararajan |
Format: | Theses and Dissertations |
Published: |
2008
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/4905 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Similar Items
-
Pruning methods for RBF networks
by: Tarannum Shakir.
Published: (2008) -
Neural network based ATM admission controller
by: Joice Yanto
Published: (2008) -
QoS and traffic shaping in ATM networks
by: Pratik Srivastava.
Published: (2008) -
Neural networks for ATM traffic control
by: Ng, Hock Soon.
Published: (2008) -
A study of traffic shaping on ATM
by: Lim, Cheng Heng.
Published: (2008)