An optimum RBF network for signal detection in non-Gaussian noise

被引：0

作者：

Khairnar, DG ^{[1
]}

Merchant, SN ^{[1
]}

Desai, UB ^{[1
]}

机构：

[1] Indian Inst Technol, Dept Elect Engn, SPANN Lab, Bombay 400076, Maharashtra, India

来源：

PATTERN RECOGNITION AND MACHINE INTELLIGENCE, PROCEEDINGS | 2005年 / 3776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：

In this paper, we propose a radial basis function (RBF) neural network for detecting a known signal in the presence of non-Gaussian and Gaussian noise. In case of non-Gaussian noise, our study shows that RBF signal detector has significant improvement in performance characteristics; detection capability is better to those obtained with multilayer perceptrons (MLP) and the matched filter (MF) detector.

引用

页码：306 / 309

页数：4

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