Multilayer Feedforward Neural Networks

BP (Back-Propagation algorithm) and GA (Genetic Algorithm) are among the most effective algorithms of neural networks (NN). As a deterministic gradient-descent algorithm and a stochastic optimizing algorithm respectively, there exits great compensability between their advantages and disadvantages. The proposed hybrid BP/GA learning method f0r a multilayer feedforward net blends the merits of both BP and GA. Based on BP/GA, a two-layer feedforward neural network is designed. HSPICE simulation results have proved its ability to solve the XOR problem.