Nonlinear optimization using a modified Hopfield model
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Data
1998-01-01
Autores
da Silva, I. N.
de Arruda, LVR
do Amaral, W. C.
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Institute of Electrical and Electronics Engineers (IEEE)
Resumo
Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements. Neural networks with feedback connections provide a computing model capable of solving a rich class of optimization problems. In this paper, a modified Hopfield network is developed for solving constrained nonlinear optimization problems. The internal parameters of the network are obtained using the valid-subspace technique. Simulated examples are presented as an illustration of the proposed approach.
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IEEE World Congress on Computational Intelligence. New York: IEEE, p. 1629-1633, 1998.