A novel cluster method in fuzzy neural networks
Deqiang Li, Shabai Huang · 2003
Ching-chang Wong et. al(1999) proposed a cluster method to make training sample data stepwise converge to cluster centers regardless of the predetermination of center number. This paper improves the cluster method, and proves its convergence by using Brouwer fixed point theorem. Based on the result of the cluster method, one first order TSK fuzzy neural network is established and a hybrid algorithm is implemented to tune network parameters. Finally, simulation results are given to demonstrate the effectiveness of this cluster method in fuzzy neural networks.