M. Marchesi, G. Orlandi, F. Piazza, G. Pignotti, A. Uncini  Home/Search
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Abstract: In this paper a new method is presented to dynamically adapt the topology of a neural network using only the information of the learning set. The proposed algorithm eliminates connections from an initial fully connected network and presents some characteristics which can resemble some behaviour of the biological networks like the so-called critical period. Preliminary experimental results are presented which prove the effectiveness of the proposed algorithm. (Update)
Context of citations to this paper: More
...its internal topology. These changes are driven by either the received external stimuli and the pre existent connection layout. In [ 13], it has been shown how a similar idea can be applied to fully connected artificial neural networks. In this paper, a pruning algorithm for...
Cited by: More
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BibTeX entry: (Update)
M. MARCHESI, O. ORLANDI, F. PIAZZA, G. PIGNOTTI, A. UNCINI, "Dynamic topology neural network", in Parallel Architectures and Neural Networks III, E.R. Caianiello, Ed. World Scientific, 1990, pp. 107-. 115 http://citeseer.ist.psu.edu/marchesi90dynamic.html More
@misc{ marchesi90dynamic,
author = "M. MARCHESI and O. ORLANDI and F. PIAZZA and G. PIGNOTTI and A. UNCINI",
title = "Dynamic topology neural network",
text = "M. MARCHESI, O. ORLANDI, F. PIAZZA, G. PIGNOTTI, A. UNCINI, Dynamic topology
neural network, in Parallel Architectures and Neural Networks III, E.R.
Caianiello, Ed. World Scientific, 1990, pp. 107-. 115",
year = "1990",
url = "citeseer.ist.psu.edu/marchesi90dynamic.html" }
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