[1]郑陶冶,高翔.一种基于混合遗传算法的有源噪声控制方法[J].东南大学学报(自然科学版),2004,34(2):171-174.[doi:10.3969/j.issn.1001-0505.2004.02.007]
 Zheng Taoye,Gao Xiang.Active noise control method based on hybrid genetic algorithms[J].Journal of Southeast University (Natural Science Edition),2004,34(2):171-174.[doi:10.3969/j.issn.1001-0505.2004.02.007]
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一种基于混合遗传算法的有源噪声控制方法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
34
期数:
2004年第2期
页码:
171-174
栏目:
信息与通信工程
出版日期:
2004-03-20

文章信息/Info

Title:
Active noise control method based on hybrid genetic algorithms
作者:
郑陶冶 高翔
东南大学无线电工程系, 南京 210096
Author(s):
Zheng Taoye Gao Xiang
Department of Radio Engineering, Southeast University, Nanjing 210096, China
关键词:
混合遗传算法 自适应滤波 有源噪声控制
Keywords:
hybrid genetic algorithm adaptive filtering active noise control
分类号:
TN911
DOI:
10.3969/j.issn.1001-0505.2004.02.007
摘要:
提出了一种基于混合遗传算法的格型IIR滤波器结构的有源噪声控制方法.混合遗传算法将遗传算法与随机搜索算法结合起来,可以改善基本遗传算法的局部搜索能力,克服基本遗传算法存在未成熟收敛问题.本文选择UNDX交叉算子作为遗传算法的主要算子,在保留当前最佳个体的同时,再对该最佳个体用随机搜索法搜索优化个体.这样既保证了算法的全局收敛性,又提高了收敛速度.仿真结果表明,该算法可以有效地实现噪声控制.
Abstract:
A hybrid genetic algorithm(HGA)is presented for an active noise control(ANC)method with a lattice IIR filter. The HGA approach combines the genetic algorithm with the stochastic search algorithm to improve the local-search properties and overcome the premature convergence of the standard genetic algorithm(SGA). A real-coded genetic algorithm is adopted using the unimodal normal distribution crossover(UNDX)and the elitist model. And then, the stochastic search algorithm is used to optimize the elitist. This approach maintains the globe-search properties of the GA and improves the convergence speed. Simulation experiments show that the results of the application in active noise control is satisfactory.

参考文献/References:

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[4] 陈国良,王煦法,庄镇泉,等.遗传算法及其应用[M].北京:人民邮电出版社.1996.1-25.
[5] Yim Kook Hyun,Kim Jong Boo,Lee Tae Pyo,et al.Genetic adaptive IIR filtering algorithm for active noise control[A].In:1999 IEEE International Fuzzy Systems Conference Proceedings[C].Seoul,1999.1723-1728.
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备注/Memo

备注/Memo:
基金项目: 国家自然科学基金资助项目(60372053)、江苏省应用基础研究资助项目(BJ98002)、东南大学优秀青年教师教学科研资助计划.
作者简介: 郑陶冶(1974—),男,硕士生; 高翔(联系人),男,博士,副教授,xianggao@seu.edu.cn.
更新日期/Last Update: 2004-03-20