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...

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Main Author: Mohit Aiyar
Other Authors: Narasimhan Sundararajan
Format: Theses and Dissertations
Published: 2008
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Online Access:https://hdl.handle.net/10356/4905
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-49052023-07-04T17:00:02Z Growing and pruning (GAP) RBF networks for call admission control in ATM traffic management Mohit Aiyar Narasimhan Sundararajan School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems DRNTU::Engineering::Computer science and engineering::Computing methodologies 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 minimal radial basis function neural network by adding and pruning hidden neurons based on input data and are ideal for online adaptive control of fast time-varying non-linear systems. The use of GAP and MRAN in the study of call admission control schemes is new. The fast learning and accurate predictions obtained with the neural networks are shown to make better call admission control decisions under heavy traffic situations compared to conventional schemes. MASTER OF ENGINEERING (EEE) 2008-09-17T10:01:08Z 2008-09-17T10:01:08Z 2005 2005 Thesis Mohit, A. (2005). Growing and pruning (GAP) RBF networks for call admission control in ATM traffic management. Master’s thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/4905 10.32657/10356/4905 Nanyang Technological University application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
topic DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
DRNTU::Engineering::Computer science and engineering::Computing methodologies
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
DRNTU::Engineering::Computer science and engineering::Computing methodologies
Mohit Aiyar
Growing and pruning (GAP) RBF networks for call admission control in ATM traffic management
description 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 minimal radial basis function neural network by adding and pruning hidden neurons based on input data and are ideal for online adaptive control of fast time-varying non-linear systems. The use of GAP and MRAN in the study of call admission control schemes is new. The fast learning and accurate predictions obtained with the neural networks are shown to make better call admission control decisions under heavy traffic situations compared to conventional schemes.
author2 Narasimhan Sundararajan
author_facet Narasimhan Sundararajan
Mohit Aiyar
format Theses and Dissertations
author Mohit Aiyar
author_sort Mohit Aiyar
title Growing and pruning (GAP) RBF networks for call admission control in ATM traffic management
title_short Growing and pruning (GAP) RBF networks for call admission control in ATM traffic management
title_full Growing and pruning (GAP) RBF networks for call admission control in ATM traffic management
title_fullStr Growing and pruning (GAP) RBF networks for call admission control in ATM traffic management
title_full_unstemmed Growing and pruning (GAP) RBF networks for call admission control in ATM traffic management
title_sort growing and pruning (gap) rbf networks for call admission control in atm traffic management
publishDate 2008
url https://hdl.handle.net/10356/4905
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