摘要
本文提出了一种特殊的模糊联想记忆系统（ＦＡＭ）─正则模糊联想记忆及其学习算法─正则化学习算法．正则模糊联想记忆具有比一般方法所设计的模糊联想记忆更好的性能，且其性能受训练数据不足和训练数据噪声的影响很小．最后，举例说明了正则模糊联想记忆在模糊控制器中的应用．
A special kind of fuzzy associative memory system (FAM)-regularized fuzzy associative memory and its learning algorithm-regularization learning algorithm are presented. The regularized FAM has better performance than the FAMs designed by traditional methods, with lackage of and noise in training data exerting little influence on its performance. Finally,the application of the regularized FAM in fuzzy controller is illustrated with an example.
出处
《电子学报》
EI
CAS
CSCD
北大核心
1997年第7期68-71,81,共5页
Acta Electronica Sinica
基金
国家自然科学基金
关键词
正则化
模糊联想记忆
遗传算法
模糊控制器
Regularization, Fuzzy associative memory,Genetic algorithm,Fuzzy controller
