Title :
A Novel Method to Detect and Separate LFM Signal Based on Artificial Neural Network
Author :
Chen, Enqing ; Tao, Ran
Author_Institution :
Dept. of Electron. Eng., Beijing Inst. of Technol.
Abstract :
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
Keywords :
Gaussian noise; artificial intelligence; frequency modulation; interference suppression; neural nets; signal detection; source separation; Gauss noise; artificial neural network; back-propagation algorithm; linear frequency modulation; noise elimination; signal detection; signal separation; AWGN; Additive white noise; Artificial neural networks; Chirp; Computational complexity; Computational modeling; Gaussian noise; Neural networks; Neurons; Signal processing algorithms;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1614562