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A study concerning the elimination of the neurons or of the layers from multi-layer neural network

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dc.contributor.author PUŞCAŞU, Gheorghe
dc.contributor.author CODREŞ, Bogdan
dc.date.accessioned 2019-11-13T11:21:42Z
dc.date.available 2019-11-13T11:21:42Z
dc.date.issued 2005
dc.identifier.citation PUŞCAŞU, Gheorghe, CODREŞ, Bogdan. A study concerning the elimination of the neurons or of the layers from multi-layer neural network. In: Microelectronics and Computer Science: proc. of the 4th intern. conf., September 15-17, 2005. Chişinău, 2005, vol. 2, pp. 279-287. ISBN 9975-66-038-X. en_US
dc.identifier.isbn 9975-66-038-X
dc.identifier.uri http://repository.utm.md/handle/5014/6758
dc.description.abstract After a neuronal structure is trained using a training set, an important problem is to generalise the learned. If the system memorises only the data used for the training session it might be possible, the network to give us erroneous results, for another similar set of data. This paper proposes a study concerning some techniques for the elimination of neurones from the layers of a multi-layer neural network. This procedure is applied after the training stage. The study leads us to a network structure with a smaller number of neurones and layers, structure that approximates in the same manner unlinear function. Another experimental aspect is the fact that there are neurones with outputs which are not modified when at the input of the network is presented a set vector from training sequence. In this case the neurones with the constant output will be eliminated. en_US
dc.language.iso en en_US
dc.publisher Technical University of Moldova en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject neural networks en_US
dc.subject inactive neurones en_US
dc.subject neurones en_US
dc.subject neural networks en_US
dc.title A study concerning the elimination of the neurons or of the layers from multi-layer neural network en_US
dc.type Article en_US


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