%0 Journal Article
%T An Application of Improved RBF Neural Network in Modulation Recognition<br>一种优化的RBF神经网络在调制识别中的应用
%A YE Jian
%A GE Lin-Dong
%A WU Yue-Xian
%A <br>叶健
%A 葛临东
%A 吴月娴
%J 自动化学报
%D 2007
%I 
%X In this paper, a novel modulation recognition method is proposed, which is based on an improved radial basis function (RBF) neural network. The parameters of radial basis function are obtained by fuzzy C-means (FCM) clustering algorithm, while weights of the network are trained with gradient descent approach. Optimal stopping rule is used to avoid overfitting and improve training speed as well as generalization ability. Application of this method to modulation recognition of practical signals shows satisfactory performance.
%K Modulation recognition
%K RBF neural network
%K FCM clustering algorithm
%K optimal stopping rule<br>调制识别
%K 径向基函数神经网络
%K 模糊C-均值聚类算法
%K 最优停止法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=A846D67C2AE7FF8A&yid=A732AF04DDA03BB3&vid=27746BCEEE58E9DC&iid=B31275AF3241DB2D&sid=4A8412AEEC89236B&eid=BBA8B1249CDAA6CE&journal_id=0254-4156&journal_name=自动化学报&referenced_num=0&reference_num=12