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粒子群优化算法在FIR数字滤波器设计中的应用
引用本文:李辉,张安,赵敏,徐琦.粒子群优化算法在FIR数字滤波器设计中的应用[J].电子学报,2005,33(7):1338-1341.
作者姓名:李辉  张安  赵敏  徐琦
作者单位:西北工业大学电子信息学院,陕西西安 710072
摘    要:本文针对有限脉冲响应(FIR)数字滤波器的设计实质上是一个多参数优化问题,提出了一种用粒子群优化算法(PSO)设计FIR数字滤波器的方法.首先将滤波器的设计问题转化为滤波器参数的优化问题,然后利用粒子群优化算法对整个参数空间进行高效并行搜索以获得参数的最优化.FIR数字低通、带通滤波器设计实例证明了该方法的有效性和优越性.

关 键 词:粒子群优化算法  FIR数字滤波器  滤波器设计  
文章编号:0372-2112(2005)07-1338-04
收稿时间:2004-02-26
修稿时间:2004-02-262005-02-18

Particle Swarm Optimization Algorithm for FIR Digital Filters Design
LI Hui,ZHANG An,ZHAO Min,XU Qi.Particle Swarm Optimization Algorithm for FIR Digital Filters Design[J].Acta Electronica Sinica,2005,33(7):1338-1341.
Authors:LI Hui  ZHANG An  ZHAO Min  XU Qi
Affiliation:Department of Electronic Engineering,Northwestern Polytechnical University,Xi'an,Shanxi 710072,China
Abstract:The particle swarm is an algorithm for finding optimal region of complex search spaces through the interaction of individuals in a population of particles.A new method based on particle swarm optimization(PSO) is proposed to design FIR digital filters.The design of FIR digital filters is converted into the optimization of the parameters of FIR digital filters.PSO is used to search the whole parameters space effectively and globally in order to optimize parameters.The effectiveness and superiority of the introduced method are demonstrated by experimental results on the low pass and band pass FIR digital filters.And compared with other optimization algorithms PSO has advances in computational power.
Keywords:particle swarm optimization  FIR digital filters  filter design
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