Artificial neural networks for the bipartite and k-partite subgraph problems
In , 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.
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