Research Output

An Investigation into the improvement of Local Minima of the Hopfield Network

  The paper investigates the improvement of local minima of the Hopfield network. A local minima escape algorithm (LME algorithm), is proposed for improving local minima of small-scale networks. Experiments on travelling salesman problems (TSP) show that the LME algorithm is an efficient algorithm in improving the local minima, and the comparison with the simulated annealing algorithm (SA) shows that the LME algorithm can produce better results in less time. The paper then investigates the improvement of local minima of large-scale networks. By combining the LME algorithm with a network partitioning technique, a network partitioning algorithm (NPA) is proposed. Experiments on 51 and 101-city TSP problems show that the local minima of large-scale networks can be greatly improved by the NPA algorithm, however, the global minima are still difficult to achieve.

  • Type:

    Article

  • Date:

    30 September 1996

  • Publication Status:

    Published

  • Publisher

    Elsevier

  • DOI:

    10.1016/0893-6080(96)00017-2

  • ISSN:

    0893-6080

  • Library of Congress:

    TK Electrical engineering. Electronics Nuclear engineering

  • Dewey Decimal Classification:

    621.3827 Optical communications

Citation

Peng, M., Gupta, N. K. & Armitage, A. (1996). An Investigation into the improvement of Local Minima of the Hopfield Network. Neural Networks. 9, 1241-1253. doi:10.1016/0893-6080(96)00017-2. ISSN 0893-6080

Authors

Keywords

Hopfield network; local minima; global minimum; network partitioning; travelling salesman problem;

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