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。
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.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第27期142-143,151,共3页
Computer Engineering and Applications
基金
中国博士后科学基金(No.20060390170)
山西省自然科学基金(the Natural Science Foundation of Shanxi Province of China under Grant No.20051038)
关键词
盲均衡算法
双线性反馈神经网络
收敛速度
误码率
blind equalization algorithm
Bilinear Recurrent Neural Network（BRNN）
convergence rate
Bit Error Ratio（BER）
