%0 Journal Article
%T Study on DOA estimation based on phase-angle of eigenvector using RBF neural networks<br>基于特征矢量相角的RBF神经网络DOA估计*
%A WENG Xiao-jun
%A ZHANG Min
%A LI Peng-fei
%A <br>翁晓君
%A 张旻
%A 李鹏飞
%J 计算机应用研究
%D 2011
%I 
%X In order to get the higher precision in neural network-based DOA estimation, this paper proposed a novel approach using phase-angle of eigenvector as the direction character. This approach firstly decomposed the covariance matrix to get the phase-angle of
%K phase-angle of eigenvector
%K direction character
%K DOA estimation
%K RBFNN(radial basis function nearal networks)<br>特征矢量相角
%K 方向特征
%K 来波方位估计
%K 径向基神经网络
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=0A7B6A620592A624575817C38200D904&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=DF92D298D3FF1E6E&sid=A808A3BE66628A26&eid=E6EF7D29EE8EFD11&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=11