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.

Volume

1

fYear

2005

Firstpage

32

Lastpage

35

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks and Brain, 2005. ICNN&B '05. International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-9422-4

Type

conf

DOI

10.1109/ICNNB.2005.1614562

Filename

1614562