Robust direction of arrival (DOA) estimation using RBF neural network in impulsive noise enviromnent

被引：0
|
作者：
Tang, H [1 ]
Qiu, TS [1 ]
Li, S [1 ]
Guo, Y [1 ]
Zhang, WR [1 ]
机构：
[1] Dalian Univ Technol, Sch Elect & Informat Engn, Dalian 116024, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2005, PT 3, PROCEEDINGS | 2005年 / 3498卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The DOA problem in impulsive noise environment is approached as a mapping which can be modeled using a radial-basis function neural network (RBFNN). To improve the robustness, the input pairs are preprocessed by Fractional Low-Order Statistics (FLOS) technique. The performance of this network is compared to that of the FLOM-NWSIC for both uncorrelated and correlated source. Numerical results show the good performance of the RBFNN-based DOA estimation.
引用
收藏
页码：332 / 337
页数：6
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