%0 Journal Article
%T Extreme learning machine on robust estimation<br>一种基于鲁棒估计的极限学习机方法
%A HU Yi-han
%A ZHANG Xiao-gang
%A CHEN Hu
%A LI Jing-hui
%A <br>胡义函
%A 张小刚
%A 陈　华
%A 李晶辉
%J 计算机应用研究
%D 2012
%I 
%X Extreme learning machineELM is a kind of single-hidden layer feedforword neural networksSLFNs. Comparing with traditional neural network algorithms, it is simpler in structure, with higher learning speed, and good generalization performance. The output-weight of ELM was calculated by LSEleast square estimation method. However, LSE lack of robustness, the result would be seriously damaged when there were outliers in the training data. In order to solve this problem, this paper derived a novel approach based on M-estimators of extreme learning machine called RBELM. Simulation results indicate that the RBELM proposed can significantly robust against data noise and outliers.
%K 极限学习机
%K 稳健估计
%K 鲁棒极限学习机
%K M估计
%K 神经网络
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=06EDAB79A5CA7ADD605150155D66E976&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=5D311CA918CA9A03&sid=AE5DCEB5D8E2EE2F&eid=64370E3B99885BD9&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=22