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基于遗传优化的神经网络盲均衡算法
引用本文:李沅,李凯,路旭. 基于遗传优化的神经网络盲均衡算法[J]. 中北大学学报(自然科学版), 2009, 30(2)
作者姓名:李沅  李凯  路旭
作者单位:中北大学,电子测试技术国家重点实验室,山西太原030051;西安北方惠安化学工业有限公司,陕西户县,710302
摘    要:传统前馈神经网络盲均衡中神经网络的初始权重的确定缺乏理论依据,收敛速度慢,容易陷人局部极小值.为有效克服这些缺陷,提出了遗传优化神经网络的盲均衡算法.算法用遗传算法对前馈神经网络的网络权重进行优化,为神经网络提供一个全局较优的局部搜索空间;再利用传统神经网络在这个局部空间进行更精确地搜索,最终实现盲均衡.计算机仿真结果表明:与传统神经网络算法相比,新算法达到了更好的收敛特性和均衡效果,剩余稳态误差减少30%以上,收敛速度加快约20%,误码率也有明显降低.

关 键 词:盲均衡  神经网络  BP算法  遗传算法

Blind Equalization Algorithms Based on Neural Network Optimized by Genetic Algorithm
LI Yuan,LI Kai,LU Xu. Blind Equalization Algorithms Based on Neural Network Optimized by Genetic Algorithm[J]. Journal of North University of China, 2009, 30(2)
Authors:LI Yuan  LI Kai  LU Xu
Affiliation:1.National Key Laboratory For Electronic Measurement Technology;North University of China;Taiyuan 030051;China;2.Xi'an North Huian Chemical Industry Co.;Ltd.;Huxian 710302;China
Abstract:There are some disadvantages such as slow convergence,easy local minimum and no enough theoretical evidence for determining the initial weight of neural network by the traditional FNN blind equalization algorithm.Therefore a genetic algorithm optimizing neural network(GA-BP) is proposed to overcome these disadvantages.First,a preferable local solution space is offered to the neural network by using GA.Then,a precise searching is realized in the space with the conventional neural network algorithm to finish ...
Keywords:blind equalization  neural network  BP algorithm  genetic algorithm  
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