### Self-organizing fuzzy neural network algorithm based on effective neurons

GAO Pei1, ZHAO Xin1, WANG Shitong2

1. 1.School of Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
2.School of Digital Media, Jiangnan University, Wuxi, Jiangsu 214122, China
• Online:2012-12-11 Published:2012-12-21

### 基于有效神经元的自组织模糊神经网络算法

1. 1.江南大学 物联网工程学院，江苏 无锡 214122
2.江南大学 数字媒体学院，江苏 无锡 214122

Abstract: Aimed at the problem that the low recognition rate and the poor generalization ability in traditional neural networks, an improved learning algorithm of Self-Organizing Fuzzy Neural Network（SOFNN） is presented. In this algorithm, it is as a basis for modifying, deleting and adding neurons that each neuron output and the sum of all these neurons output in the Ellipsoidal Basis Function（EBF） layer are stored. Then it can obtain effective neurons of the network and reduce the training time of samples. In order to ensure the network convergence, it uses the least square method（RLSE） to estimate the parameters and uses gradient descent method to modify the parameters. Compared with other fuzzy neural networks, the superiority in the accuracy, structure complexity and anti-jamming is effectively verified in the real data set.