基于粒子群算法的FIR滤波器的优化设计  

Optimal design of FIR filter based on the particle swarm optimization

作　　者：陈晓文[1] CHEN Xiao-wen(Department of Electronic Engineering,Fujian Polytechnic of Information Technology,Fuzhou 350003,China)

机构地区：[1]福建信息职业技术学院电子工程系

出　　处：《宁德师范学院学报（自然科学版）》2019年第3期257-262,共6页Journal of Ningde Normal University(Natural Science)

摘　　要：基于粒子群优化算法原理,将粒子群算法应用于频率采样过渡点样本的优化设计,将过渡带样本值作为优化变量,最大阻带衰减作为优化目标,并适当给过渡带样本一个较好的约束条件.仿真结果表明:利用粒子群算法优化设计的FIR滤波器与未进行优化、用查表法优化及人工群鱼算法优化设计的滤波器相比,具有更大的阻带衰减和更小的通带波动.Based on the principal of particle swarm optimization,the particle swarm optimization is applied to optimization design of the sample point in the transition.The sample values of transition bands are taken as optimization variables,maximum stop-band attenuation is taken as the optimization objective,and a better constraint condition is given to transition band samples appropriately.The results of the simulation show as follow: The FIR filter designed by particle swarm optimization method has a bigger stop-band attenuation and smaller pass-band ripple than those designed without optimization,or those optimized by table-checking method or by artificial fish swarm algorithm.

关 键 词：FIR数字滤波器 优化设计 频率采样法 粒子群优化算法 

分 类 号：TN61[电子电信—电路与系统] TP301[自动化与计算机技术—计算机系统结构]