Neural networks for ATM traffic control

This thesis presents the application of the newly developed minimal radial basis function neural network called Minimal Resource Allocation Network (MRAN) to solve the traffic control problems in Asynchronous Transfer Mode (ATM) networks. Special focus has been given to the congestion control scheme...

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Main Author: Ng, Hock Soon.
Other Authors: Sundararajan, Narasimhan
Format: Theses and Dissertations
Published: 2008
Subjects:
Online Access:http://hdl.handle.net/10356/4949
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-49492023-07-04T15:52:15Z Neural networks for ATM traffic control Ng, Hock Soon. Sundararajan, Narasimhan School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems This thesis presents the application of the newly developed minimal radial basis function neural network called Minimal Resource Allocation Network (MRAN) to solve the traffic control problems in Asynchronous Transfer Mode (ATM) networks. Special focus has been given to the congestion control scheme and the and the Available Bit Rate (ABR) flow control scheme. Master of Engineering 2008-09-17T10:02:02Z 2008-09-17T10:02:02Z 2001 2001 Thesis http://hdl.handle.net/10356/4949 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
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Ng, Hock Soon.
Neural networks for ATM traffic control
description This thesis presents the application of the newly developed minimal radial basis function neural network called Minimal Resource Allocation Network (MRAN) to solve the traffic control problems in Asynchronous Transfer Mode (ATM) networks. Special focus has been given to the congestion control scheme and the and the Available Bit Rate (ABR) flow control scheme.
author2 Sundararajan, Narasimhan
author_facet Sundararajan, Narasimhan
Ng, Hock Soon.
format Theses and Dissertations
author Ng, Hock Soon.
author_sort Ng, Hock Soon.
title Neural networks for ATM traffic control
title_short Neural networks for ATM traffic control
title_full Neural networks for ATM traffic control
title_fullStr Neural networks for ATM traffic control
title_full_unstemmed Neural networks for ATM traffic control
title_sort neural networks for atm traffic control
publishDate 2008
url http://hdl.handle.net/10356/4949
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