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

页码：332 / 337

页数：6

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