Abstract
In [1], Lee, Funabiki and Takefuji proposed a parallel algorithm for solving the bipartite subgraph problem with the maximum neural networks. In this paper, we present a new algorithm based on the discrete Hopfield network to deal with the same problem. Compared with the previous maximum neural network algorithm, our method can find solutions of same quality or better with half of neurons and much less computation time. Furthermore, for the general K-partite subgraph problem, a novel interactive Hopfield network system is devised to solve it effectively. The algorithm has been implemented and the experimental results indeed demonstrate the effectiveness of our approach.
This research was supported by the National Science Council, Taiwan, R. O. C, under Grant NSC 81-0404-E002-105.
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References
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© 1993 Springer-Verlag Berlin Heidelberg
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Lai, J.S., Ko, Y.J., Kuo, S.Y. (1993). Artificial neural networks for the bipartite and k-partite subgraph problems. In: Bode, A., Reeve, M., Wolf, G. (eds) PARLE '93 Parallel Architectures and Languages Europe. PARLE 1993. Lecture Notes in Computer Science, vol 694. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56891-3_34
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DOI: https://doi.org/10.1007/3-540-56891-3_34
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