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Deep Learning Based Radio-Signal Identification With Hardware Design

机译:基于深度学习的无线电信号识别与硬件设计

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摘要

This paper proposes a deep learning based intelligent method for detecting and identifying radio signals considering two applications: first, cognitive radar for identifying micro unmanned aerial systems and second, an automated modulation classification scheme for cognitive radio, which can be used for aeronautical communication systems. Our proposed intelligent method is designed of a spectral correlation function based feature extractor and a low-complexity deep belief network classifier with low FPGA logic utilization.
机译:本文提出了一种基于深度学习的检测和识别无线电信号的智能方法,其中考虑了两个应用:首先是用于识别微型无人机系统的认知雷达,其次是可以用于航空通信系统的认知无线电的自动调制分类方案。我们提出的智能方法是基于频谱相关函数的特征提取器和FPGA逻辑利用率低的低复杂度深度置信网络分类器而设计的。

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