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Biological Cybernetics

, Volume 72, Issue 5, pp 439–445 | Cite as

Solving the N-Queens problem with a binary Hopfield-type network

Synchronous and asynchronous model
  • Jacek Mańdziuk
Article

Abstract

The application of a discrete Hopfield-type neural network to solving the NP-Hard optimization problem — the N-Queens Problem (NQP) — is presented. The applied network is binary, and at every moment each neuron potential is equal to either 0 or 1. The network can be implemented in the asynchronous mode as well as in the synchronous one with n parallel running processors. In both cases the convergence rate is up to 100%, and the experimental estimate of the average computational complexity is polynomial. Based on the computer simulation results and the theoretical analysis, the proper network parameters are established. The behaviour of the network is explained.

Keywords

Neural Network Computer Simulation Computational Complexity Theoretical Analysis Convergence Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag 1995

Authors and Affiliations

  • Jacek Mańdziuk
    • 1
  1. 1.Institute of Mathematics, Warsaw University of TechnologyWarszawaPoland

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