基于改进型混沌粒子群优化算法的FIR高通数字滤波器设计

摘要/Abstract

摘要： 文中采用混沌粒子群算法并结合权重改进对线性相位FIR数字滤波器进行设计。将最小均方误差函数作为适应度函数,并通过优化得到线性相位FIR数字滤波器的系数。通过实例进行仿真验证,并将所提算法与最小二乘法、基本粒子群算法等进行比较。仿真结果表明,采用混沌粒子群算法设计的线性相位FIR数字滤波器具有更好的收敛特性、带通特性和阻带特性。

关键词: 参数优化, 混沌粒子群算法, 权重改进, 线性相位数字滤波器

Abstract: This paper proposed a chaos particle swarm optimization algorithm (CPSO) which combined with the weight improved to design the linear phase FIR digital filter.In this method,the minimum mean square error function is used as the fitness function,and finally the coefficient of the FIR digital filter is obtained.In order to confirm the availability of the method,CPSO algorithm was compared with the least square method and the basic PSO.The experiment results show that the FIR digital filter designed by CPSO has a better convergence,the band-pass characteristics and the stop-band characteristics.

Key words: CPSO, Line-phase FIR, Parameter optimization, Weight improved

中图分类号:

TP391

胡鑫楠. 基于改进型混沌粒子群优化算法的FIR高通数字滤波器设计[J]. 计算机科学, 2019, 46(6A): 601-604. https://doi.org/

HU Xin-nan. FIR High Pass Digital Filter Design Based on Improved Chaos Particle Swarm Optimization Algorithm[J]. Computer Science, 2019, 46(6A): 601-604. https://doi.org/

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