### Analysis of robustness of fuzzy associative memory based on Einstain’s t-norm

GAO Xiang1, MA Hengbing2

1. 1.College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108, China
2.Economic Center of Fujian Province, Fuzhou 350003, China
• Online:2014-03-01 Published:2015-05-12

### 模糊联想记忆网络的全局鲁棒性研究——基于爱因斯坦t-模

1. 1.福州大学 数学与计算机科学学院，福州 350108
2.福建省经济中心，福州 350003

Abstract: The paper analyses the robustness of learning algorithm for fuzzy associative memory based on Einstain’s t-norm by using the properties of fuzzy bidirectional associative memories based on triangular norms and the overall situation robustness of fuzzy bidirectional associative memories. The conclusion that the learning algorithm can keep good overall robustness when the perturbations are positive is proved in theory and verified by experiment in this paper. And that the learning algorithm doesn’t satisfy overall situation robustness when the noise contains negative value is proved by experiment. What is more, the relation between the maximum of perturbations of training patterns and the maximum of perturbations of the output is also analyzed and the relation curve is gotten.