摘要
本文提出了实数编码的遗传优化神经网络的盲均衡算法,有效地克服了传统前馈神经网络盲均衡的缺陷,解决了实际应用中存在神经网络的初始权重的确定缺乏理论依据的问题,提高了前馈神经网络盲均衡的均衡性能.
In this paper, genetic algorithm （GA） which is good at global searching optimizing neural network （GA-BP） is proposed as a new blind equalization method. Because of optimizing the weights of network ,the new algorithms overcome the default of traditional FNN blind equalization, solve the problem that there is no enough theoretical evidence on the determination of initial weights and improve the performance of equalization obviously.
出处
《山西大同大学学报（自然科学版）》
2008年第6期43-45,48,共4页
Journal of Shanxi Datong University(Natural Science Edition)
关键词
盲均衡
神经网络
BP算法
遗传算法
blind equalization
neural network
BP algorithm
genetic algorithm
