A constructive learning algorithm based on back-propagation

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Bibliographic Details
Title: A constructive learning algorithm based on back-propagation
Authors: Lowton, Andrew D.
Publisher Information: Aston University, 1995.
Publication Year: 1995
Collection: Aston University
Subject Terms: 003.5, Computer Science
Description: There are been a resurgence of interest in the neural networks field in recent years, provoked in part by the discovery of the properties of multi-layer networks. This interest has in turn raised questions about the possibility of making neural network behaviour more adaptive by automating some of the processes involved. Prior to these particular questions, the process of determining the parameters and network architecture required to solve a given problem had been a time consuming activity. A number of researchers have attempted to address these issues by automating these processes, concentrating in particular on the dynamic selection of an appropriate network architecture. The work presented here specifically explores the area of automatic architecture selection; it focuses upon the design and implementation of a dynamic algorithm based on the Back-Propagation learning algorithm. The algorithm constructs a single hidden layer as the learning process proceeds using individual pattern error as the basis of unit insertion. This algorithm is applied to several problems of differing type and complexity and is found to produce near minimal architectures that are shown to have a high level of generalisation ability. (DX 187, 339)
Document Type: Electronic Thesis or Dissertation
Language: English
DOI: 10.48780/publications.aston.ac.uk.00010663
Access URL: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.281835
Accession Number: edsble.281835
Database: British Library EThOS
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