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A Novel Method to Detect and Separate LFM Signal Based on Artificial Neural Network

机译:一种基于人工神经网络的检测和分离LFM信号的新方法

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摘要

A novel method using artificial neural network with back-propagation algorithm to detect and separate LFM signal is proposed. This method trains the network by LFM signal mixed with Gauss noise. Simulation result shows the trained BP neural network can eliminate noise effectively. In addition, if the learning sample is a multicomponent LFM signal, the trained network can separate the LFM signal component conveniently. Theoretical analysis and simulation results show that the proposed method has low computational complexity and good performance.
机译:提出了一种利用具有反向传播算法检测和分离LFM信号的人工神经网络的新方法。该方法通过与高斯噪声混合的LFM信号训练网络。仿真结果表明,训练有素的BP神经网络可以有效地消除噪声。另外,如果学习样本是多组分LFM信号,则训练网络可以方便地分离LFM信号分量。理论分析和仿真结果表明,该方法的计算复杂性低,性能良好。

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