期刊文献+

模拟调制信号的神经网络识别方法 被引量:3

下载PDF
导出
摘要 本文提出模拟调制信号的人工神经网络识别方法,从信息幅度、相位、频率及功率谱等特 提取四种特征参数,用于训练神经网络对模拟调制信号的识别。采用神经网络,不仅可提高识别的智能化,而且能提高正确识别率。该算法的识别性能明显高于目前广泛采用的各种方法,实验表明信噪比为8dB时,对各类模拟调制信号的正确识别率在96%以上。算法能识别的调制类型多,包括AM、DSB、USB、LSB、VSB、FM。
出处 《电子对抗》 1998年第3期13-18,共6页 Electronic Warfare
  • 相关文献

同被引文献17

  • 1Bernard Mulgrew. Applying radial basis functions[J]. IEEE Signal Processing Magazine, 1996, 13(2) :50--65.
  • 2Licheng Jiao, Lei Wang. A novel genetic algorithm based on immunity [J. IEEE Trans on Systems,M an and Cybernetics, 2000,30 (5) : 552 -- 561.
  • 3Moody J, Darken C. Fast learning in networks of locally-turned processing units[J]. Neural Computation, 1989, 6(1):281-294.
  • 4Karayiannis N B, Mi G W. Growing radial basis neural networks: merging supervised and unsupervised learning with network growth techniques[J].IEEE Trans on Neural Networks, 1997,8(6) : 1492-1506.
  • 5Yao Xin, Liu Yong. New evolutionary system for evolving artifical neural networksp[J]. IEEE Trans on Neural Networks, 1997, 8(3) :694-713.
  • 6Broomhead D S, Lowe D. Multivariable functional interpolation and adaptive networks[J]. Complex System, 1988, 11(2):321--355.
  • 7De Castro L N, Von Zuben F J. An immunological approach to initialize centers of radial basis function neural networks [A]. Proceedings of V Brazilian Conference on Neural Networks[C]. 2001.79-84.
  • 8Angeline P J, Saunders G M, Pollack J B. An evolutionary algorithm that constructs recurrent neural networks [J]. IEEE Trans on Neural Networks, 1994, 5(1): 54-64.
  • 9Ho K C, Prokopiw W, Chan Y T. Modulation identification by the wavelet transform [A]. Proc MILCOM'95[C]. 1995. 886-890.
  • 10Nandi A K, Azzouz E E. Algorithm for automatic modulation recognition of communication signals [J]. IEEE Trans on Communication, 1998, 46(4): 431-436.

引证文献3

二级引证文献13

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部