Influences of Perturbation of Training Pattern Pairs on Monolithic Fuzzy Neural Networks
Weihong Xu · Journal of Nanjing University of Science and Technology · 2009
Small perturbations of training pattern pairs may cause some disadvantages to performance of a fuzzy neural network(FNN),and a new concept is established for the robustness of a monolithic fuzzy neural network(MFNN) to perturbations of training pattern pairs.When the training pattern pairs come into the keep-order perturbations,the robustness of MFNN model is analyzed.The concept for the robustness of a FNN to perturbations of training pattern pairs can be defined similarly.The theoretical studies show that the MFNN has good robustness with h=5 when the training pattern pairs come into the γ keep-order perturbations,which is beneficial to the performance analyses,the choice of learning algorithms,and the acquisition of pattern pairs of MFNN.