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The Development and Analysis of Analytic Method as Alternative for Backpropagation in Large-Scale Multilayer Neural Networks
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Arts, Department of Game Design.
2014 (English)In: ADVCOMP 2014, The Eighth International Conference on Advanced Engineering Computing and Applications in Sciences, 2014, 46-49 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a least-square based analytic solution of the weights of a multilayer feedforward neural network with a single hidden layer and a sigmoid activation function, which today constitutes the most common type of artificial neural networks. This solution has the potential to be effective for large-scale neural networks with many hidden nodes, where backpropagation is known to be relatively slow. At this stage, more research is required to improve the generalization abilities of the proposed method.

Place, publisher, year, edition, pages
2014. 46-49 p.
Keyword [en]
analytic; FNN; large-scale; least square method; neural network; sigmoid
National Category
Computer Systems
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:uu:diva-235742ISBN: 978-1-61208-354-4 (print)OAI: oai:DiVA.org:uu-235742DiVA: diva2:761789
Conference
The Proceedings of the Eighth International Conference on Advanced Engineering Computing and Applications in Sciences, ADVCOMP 2014, Rome, Italy, August 2014
Available from: 2014-11-07 Created: 2014-11-07 Last updated: 2014-11-10

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The Development and Analysis of Analytic Method as Alternative for Backpropagation in Large-Scale Multilayer Neural Networks

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Fridenfalk, Mikael

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