%0 Journal Article
%T Fast parameter learning algorithm for fuzzy neural networks<br>一种模糊神经网络的快速参数学习算法
%A CHEN Fei
%A JING Zhong-liang
%A YAO Xiao-dong
%A <br>陈 非
%A 敬忠良
%A 姚晓东
%J 控制理论与应用
%D 2002
%I 
%X A novel parameter learning algorithm for fuzzy neural networks (FNN) is proposed. The conventional methods usually use the gradient descent based backpropogation algorithm to adjust the center and width of the membership functions. To avoid the inborn problem of BP algorithm, such as local minima and slow convergence, a modified RLS method is employed here to adjust the parameters of FNN, which is faster than the conventional BP algorithm. The validity of this method has been demonstrated by simulation results.
%K T-S fuzzy inference system
%K multi-layer neural networks
%K modified RLS algorithm
%K fuzzy neural networks (FNN)<br>T-S模糊推理系统
%K 多层前向神经网络
%K 改进RLS算法
%K 模糊神经网络
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=AB89B78392D28EA1&yid=C3ACC247184A22C1&vid=2A8D03AD8076A2E3&iid=E158A972A605785F&sid=7882A2973AA04DE8&eid=D5970ECA7D10A7B1&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=9&reference_num=7