Neural network system for determining optimal solution

Abstract

A neural network system includes an input unit, an operation control unit, a parameter setting unit, a neural network group unit, and a display unit. The network group unit includes first and second neural networks. The first neural network operates according to the mean field approximation method to which the annealing is added, whereas the second neural network operates in accordance with the simulated annealing. Each of the first an second neural networks includes a plurality of neurons each connected via synapses to neurons so as to weighting outputs from the neurons based on synapse weights, thereby computing an output related to a total of weighted outputs from the neurons according to an output function. The parameter setting unit is responsive to a setting instruction to generate neuron parameters including synapse weights, threshold values, and output functions, which are set to the first neural network and which are selective set to the second neural network. The operation control unit responsive to an input of a problem analyzes the problem and then generates a setting instruction based on a result of the analysis to output the result to the parameter setting unit. After the neuron parameters are set thereto, in order for the first and second neural network to selectively or to iteratively operate, the operation control unit controls operations of computations in the network group unit in accordance with the analysis result and then presents results of the computations in the network group unit on the display unit.