An adaptive beamforming approach using online learning neural network

被引：1
|
作者：
Sun, XB [1 ]
Zhong, SS [1 ]
机构：
[1] Shanghai Univ, Sch Commun & Informat Engn, Shanghai 200072, Peoples R China
来源：
IEEE ANTENNAS AND PROPAGATION SOCIETY SYMPOSIUM, VOLS 1-4 2004, DIGEST | 2004年
关键词：
D O I：
10.1109/APS.2004.1331922
中图分类号：
TN [电子技术、通信技术];
学科分类号：
0809 ;
摘要：
This paper proposes a new approach for the adaptive beamforming of an antenna array using online learning based radial basis function (RBF) neural network, The number of hidden layer nodes can be increased or decreased on line, and the function's centers and widths of the RBF network can be adaptively modified. This network has better generalization performance than that of the conventional K-mean based RBF network. Simulated examples confirm the validity of this method.
引用
收藏
页码：2663 / 2666
页数：4
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