A proposal of competition resolution methods on the maximum neuron model through N-queens problems

The maximum neuron model provides efficient neural network solutions for combinatorial optimization problems. In this ‘winner-take-all’ model, one and only one neuron with the maximum input value is always fired in each group of neurons to satisfy the selection constraint. The maximum neuron model can not only limit the searching space, but also reduce the computation load. In this paper, we propose two methods for selecting one neuron among two or more neurons which have the same maximum input value, named ‘least index method’ and ‘previous selection method’. The simulation results in N-queens problems show that the latter method performs better than the former method generally, and that the previous selection method on the N-parallel mode provides the suitable algorithm for hardware implementation of large-scale neural networks.