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Volume 24 Issue 5
May  2002
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Li Tiejun, Wang He, Xiao Xianci. Recognition of modulation signal based on a new method of feature selection[J]. Journal of Electronics & Information Technology, 2002, 24(5): 661-666.
Citation: Li Tiejun, Wang He, Xiao Xianci. Recognition of modulation signal based on a new method of feature selection[J]. Journal of Electronics & Information Technology, 2002, 24(5): 661-666.

Recognition of modulation signal based on a new method of feature selection

  • Received Date: 2000-06-20
  • Rev Recd Date: 2001-01-08
  • Publish Date: 2002-05-19
  • According to the characteristic of communication signals, a new method of feature selection is presented. In this method, the efficient and robust genetic algorithm is used to sift out qualified feature subset, under the rule of clustering level of same classifications and separating level of different classifications. With the fine structure of evidence theory, a considerable recognition ratio is obtained under a wide range of SNR environment. Finally, the effectiveness of this method is proved by computer simulation.
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  • Lu Mingquan, Xiao Xianci, Li Lemin, A new digital modulation recognition method using features extracted from GAR model parameters, Journal of Electronics(China), 1999, 16(3), 244-250.[2]K. Assaleh.[J].K. Farrall, R. J. Mammone, A new method of modulation classification for digitally modulated signals, Proc. MILCOM92, San Diego, CA.0712,1992:-[3]E.E. Azzouz, A. K. Nandi, Automatic identification of digital modulation types, Signal Processing, 1995, 47(4), 55-69.[4]R. Setiono, H. Liu, Neural-network feature selector, IEEE Trans. on Neural Networks, 1997,NN-8(3), 654-661.[5]吕铁军,魏平,肖先赐,基于分形和测度理论的信号调制识别,电波科学学报,2001,16(1),123-127[6]M. Srinivas, L. M. Patnaik, Genetic algorithms: A Survey, Computer, 1994, 6(2), 17-26.[7]S.C.A. Thomopoulos, Sensor integration and data fusion, Journal of Robotic Systems, 1990,7(3), 337-372.[8]张尧庭,杜劲松,人工智能中的概率统计方法,北京,科学出版社,1998,31-35.[9]肖先赐,吕铁军,通信信号特征分析研究,研究报告,成都,电子科技大学,1998.
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