%0 Journal Article
%T Back-propagation algorithm with magnified error signals<br>一种放大误差信号的BP算法
%A CHENG Yue
%A LIU Qiong-sun
%A <br>程玥
%A 刘琼荪
%J 计算机应用研究
%D 2011
%I 
%X In view of the BP neural network existence convergence rate slow and easy to fall into local minimum, this paper presented a back-propagation (BP) algorithm with fast convergence. The new algorithm magnified the error signals by modi-fying the derivative of the activation function. This paper analyzed the convergence proof of the algorithm and compared the magnified algorithm with the standard BP algorithm and the improved algorithm of NG et al in the test. Simulation results show that the magnified algorithm can be more effective than the other two algorithms. It speeds up the convergence rate and enhances the global convergence capability.
%K 后向反馈算法
%K 误差信号
%K 收敛性
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=68AFB5AAC32788BC1746EEC750F8DF1B&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=0B39A22176CE99FB&sid=652E7E360EBE3082&eid=BB98BB04E861B6F5&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=7