Learning capabilities of neural networks

Learning capabilities of neural networks

Up to now many neural network models have been proposed. In our study we focus on two kinds of feedforward networks: strictly feedforward networks and Kohonen's self-organizing mappings where lateral competition is introduced. The two kinds of feedforward networks have played a fundamental role...

Full description

Saved in:
Bibliographic Details
Main Author: Huang, Guangbin.
Other Authors: School of Electrical and Electronic Engineering
Format: Theses and Dissertations
Language:English
Published: 2008
Subjects:
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Online Access:http://hdl.handle.net/10356/13161
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-13161
record_format dspace
spelling sg-ntu-dr.10356-131612023-07-04T15:28:57Z Learning capabilities of neural networks Huang, Guangbin. School of Electrical and Electronic Engineering Haroon A Babri DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Up to now many neural network models have been proposed. In our study we focus on two kinds of feedforward networks: strictly feedforward networks and Kohonen's self-organizing mappings where lateral competition is introduced. The two kinds of feedforward networks have played a fundamental role in neural networks research and application. Doctor of Philosophy (EEE) 2008-08-26T04:29:08Z 2008-10-20T07:16:48Z 2008-08-26T04:29:08Z 2008-10-20T07:16:48Z 1998 1998 Thesis http://hdl.handle.net/10356/13161 en 182 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Huang, Guangbin.
Learning capabilities of neural networks
description Up to now many neural network models have been proposed. In our study we focus on two kinds of feedforward networks: strictly feedforward networks and Kohonen's self-organizing mappings where lateral competition is introduced. The two kinds of feedforward networks have played a fundamental role in neural networks research and application.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Huang, Guangbin.
format Theses and Dissertations
author Huang, Guangbin.
author_sort Huang, Guangbin.
title Learning capabilities of neural networks
title_short Learning capabilities of neural networks
title_full Learning capabilities of neural networks
title_fullStr Learning capabilities of neural networks
title_full_unstemmed Learning capabilities of neural networks
title_sort learning capabilities of neural networks
publishDate 2008
url http://hdl.handle.net/10356/13161
_version_ 1772825277797236736

Similar Items