Influence of Perturbations of Training Pattern Pairs on Stability of Polygonal Fuzzy Neural Network
Sui Xiao · 2012
The concepts of the maximum perturbation error of polygonal fuzzy numbers and γ-perturbation of training pattern pairs are put forward,and the learning algorithm of connection weight is designed according to error-correction rules by introducing polygonal fuzzy numbers and their operations.Then the definition of the global stability of the polygonal fuzzy neural networks of the perturbation of training pattern pairs is introdued.Secondly,whenever the transfer function satisfies the Lipschitz condition and γ-perturbation occurs in the training pattern pairs,the stability of the connections of the three-layer polygonal fuzzy neural networks is proved by applying mathematical induction.Moreover,that the γ-perturbation of this network with respect to the training pattern pairs possesses the global stability is obtained.Finally,the influence of perturbations of training pattern pairs on the stability of polygonal fuzzy neural networks is explained by the simulative examples.