CONVERGENCE TIME ON THE RS MODEL FOR NEURAL NETWORKS

T.J.P. Penna, P.M.C. de OLIVEIRA, J.J. Arenzon, R.M.C. de ALMEIDA and J.R. Iglesias
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T.J.P. Penna: Instituto de Física, Universidade Federal Fluminense, C.P. 100296, 24020 - Niterói, RJ, Brazil
P.M.C. de OLIVEIRA: Instituto de Física, Universidade Federal Fluminense, C.P. 100296, 24020 - Niterói, RJ, Brazil
J.J. Arenzon: Instituto de Física, Universidade Federal do Rio Grande do Sul, C.P. 15051, 91500 - Porto Alegre, RS, Brazil
R.M.C. de ALMEIDA: Instituto de Física, Universidade Federal do Rio Grande do Sul, C.P. 15051, 91500 - Porto Alegre, RS, Brazil
J.R. Iglesias: Instituto de Física, Universidade Federal do Rio Grande do Sul, C.P. 15051, 91500 - Porto Alegre, RS, Brazil

International Journal of Modern Physics C (IJMPC), 1991, vol. 02, issue 03, 711-717

Abstract: Convergence times and the corresponding dispersions have been studied numerically as parameters to measure the efficiency of neural network models. These quantities are also supposed to be related to the number of spurious states for each configuration of stored patterns. In this work we measure these quantities for a recent multineuron interaction model presenting an enhanced performance compared to other traditional schemes.

Keywords: Neural Networks; Multispin Coding; Multineuron Models (search for similar items in EconPapers)
Date: 1991
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DOI: 10.1142/S0129183191000950

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