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

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 th...

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Bibliographic Details
Main Authors: EnQing Chen, Ran Tao
Format: Conference Proceeding
Language:English
Subjects:
Additive white noise
Artificial neural networks
AWGN
Chirp
Computational complexity
Computational modeling
Gaussian noise
Neural networks
Neurons
Signal processing algorithms
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Summary: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
DOI:10.1109/ICNNB.2005.1614562