Dynamic fuzzy neural network (D-FNN)

whose basic idea is to construct a RBF neural network based on extension

could be seen as a TSK fuzzy system

as well as a Gaussian RBF neural network based on normalized. In the algorithm proposed

fuzzy neural network does not need to be predetermined before learning. During the process of learning

parameter estimation and structure identification are done simultaneously

and a fuzzy rule would be automatically generated or deleted

according to the system accuracy requirement and importance of fuzzy rules

Simulated experiments are performed in terms of learning speed

system structure and the generalization ability.The results show that D-FNN has more concise structure and more excellent performance.