Model of NW Multilayer Feedforward Small-World Artificial Neural Networks and It's Applied

To find the optimal neural network structure,based on the research methods from the complex network,the structure of multi-layer forward neural networks model was studied,and a new neural networks model,NW multi-layer forward small world artificial neural networks was proposed,whose structure of layer was between the regular model and the stochastic model.At first,the regular of multilayer feed-forward neural network neurons randomized cross-layer link back layer with a probability p,and constructed the new neural network model.Secondly,the cross-layer small world artificial neural networks were used for function approximation under different re-wiring probability.The count of convergence under different probability was compared by setting a same precision.Simulation shows that the small-world neural network has a better convergence speed than regular network and random network nearly p=0.08,and the optimum performance of the NW multi-layer forward small world artificial neural network is proved in the right side of probability increases.