计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (33): 83-85.DOI: 10.3778/j.issn.1002-8331.2008.33.026

• 研发、设计、测试 • 上一篇    下一篇

粒子群优化算法在FIR数字滤波器设计中的应用

周飞红1,2,刘 辉1,廖子贞3   

  1. 1.湖南师范大学 物理与信息科学学院,长沙 410081
    2.湖南涉外经济学院 实验中心,长沙 410205
    3.长沙理工大学 计算机与通信工程学院,长沙 410077
  • 收稿日期:2007-12-13 修回日期:2008-03-18 出版日期:2008-11-21 发布日期:2008-11-21
  • 通讯作者: 周飞红

FIR digital filter design and its application based on Particle Swarm Optimization algorithm

ZHOU Fei-hong1,2,LIU Hui1,LIAO Zi-zhen3   

  1. 1.College of Physics and Information Science,Hunan Normal University,Changsha 410081,China
    2.Laboratory Center of Hunan International Economics University,Changsha 410205,China
    3.Computer and Communication Engineering College,Changsha University of Science & Technology,Changsha 410077,China
  • Received:2007-12-13 Revised:2008-03-18 Online:2008-11-21 Published:2008-11-21
  • Contact: ZHOU Fei-hong

摘要: 介绍了基于粒子群优化算法的FIR数字滤波器的设计方法,并用该方法设计了一个高通滤波器。与用Parks-McClellan算法设计的高通滤波器进行了对比,发现基于粒子群优化算法的FIR滤波器的通带波动更小,阻带衰减更大。将用这两种算法设计的滤波器作用于混频信号,得出的结果也证明了基于粒子群优化算法的FIR滤波器的有效性。

Abstract: In this paper,the design of FIR filters based on Particle Swarm Optimization algorithm are introduced,and a high-pass filter has been designed by this method.Comparing with the Parks-McClellan algorithm,the FIR digital filter designed by PSO algorithm has smaller pass-band ripple and bigger stop-band attenuation.The effectiveness and superiority of the introduced method are demonstrated by the experimental results on the mixed-signal which is filtered by these two filters designed by these two algorithm.