Neural network application in automatic recognition of communication signals

Author

Jian, Chen ; Yonghong, Kuo ; Jiandong, Li ; Fenglin, Fu

Author_Institution

Sch. of Commun. Eng., Xidian Univ., Xi´´an, China

fYear

2003

fDate

27-30 Sept. 2003

Firstpage

457

Lastpage

462

Abstract

Automatic recognition of modulated signals has seen increasing demand nowadays. The use of artificial neural networks (NNs) for the purpose has been popular since the late 90´s. This paper proposes radial basis functions (RBF) to perform the recognition of eight kinds of modulated signals. Design considerations for the NN recognition are discussed. Computer simulation results show that the overall success rate is over 93% at the signal-to-noise ratio (SNR) of 6 dB, and the overall success rate is over 96% at the SNR of 10 dB.

Keywords

neural nets; noise; pattern recognition; radial basis function networks; signal processing; telecommunication signalling; NN recognition; RBF; SNR; artificial neural network; automatic recognition; communication signal recognition; modulated signal; neural network application; radial basis function; signal-to-noise ratio; Application software; Artificial neural networks; Computational intelligence; Computer simulation; Feature extraction; Flowcharts; Intelligent networks; Neural networks; Signal processing; Signal to noise ratio;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Multimedia Applications, 2003. ICCIMA 2003. Proceedings. Fifth International Conference on

Print_ISBN

0-7695-1957-1

Type

conf

DOI

10.1109/ICCIMA.2003.1238169

Filename

1238169