计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (27): 142-143.

• 网络、通信与安全 • 上一篇    下一篇

基于双线性反馈神经网络盲均衡算法的研究

张立毅1,2,刘 婷2,孙云山2,李 锵1,滕建辅1,2   

  1. 1.天津大学 电子信息工程学院,天津 300072
    2.天津商学院 信息工程学院,天津 300134
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-09-21 发布日期:2007-09-21
  • 通讯作者: 张立毅

Research of blind equalization algorithm based on bilinear recurrent neural network

ZHANG Li-yi1,2,LIU Ting2,SUN Yun-shan2,LI Qiang1,TENG Jian-fu1,2   

  1. 1.School of Electric Information Engineering,Tianjin University,Tianjin 300072,China
    2.College of Information Engineering,Tianjin University of Commerce,Tianjin 300134,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-09-21 Published:2007-09-21
  • Contact: ZHANG Li-yi

摘要: 将双线性反馈神经网络应用于盲均衡算法,提出了一种新的基于双线性反馈神经网络盲均衡算法,推导出算法迭代公式,计算机仿真表明,新算法具有较快的收敛速度和较小的误码率。

关键词: 盲均衡算法, 双线性反馈神经网络, 收敛速度, 误码率

Abstract: Bilinear recurrent neural network was applied in blind equalization algorithm.A new blind equalization algorithm based on Bilinear Recurrent Neural Network(BRNN) was proposed.Iteration formula was reduced.Simulation results show that this algorithm could converge quickly and had the less bit error ratio.

Key words: blind equalization algorithm, Bilinear Recurrent Neural Network(BRNN), convergence rate, Bit Error Ratio(BER)