FIR滤波器的分组并行粒子群优化算法设计

FIR Filter Design based on Grouping Parallel Particle Swarm Optimization Algorithm

根据FIR滤波器幅频响应特性,采用分组并行粒子群算法计算滤波器的系数,在粒子搜索过程中进行分组和并行化处理,以防止算法出现早熟同时又能提高算法的收敛速度。该算法搜索的滤波器系数,能使FIR滤波器幅频响应与理想幅频响应之间的均方误差最小。文章以低通滤波器设计为例进行了仿真,从仿真结果可以看出,分组并行粒子群优化算法设计的FIR滤波器具有运算量小、速度快和性能好等优点。

The FIR filter design method based on grouping parallel particle swarm optimization algorithm,According to the FIR filter＇s amplitude-frequency response characteristics,calculates filter coefficients by using grouping parallel particle swarm algorithm.The particles are grouped and paralleled processing in search process,in order to prevent premature while algorithms improve the convergence speed.The frequency response can get the minimum mean square error between the designed FIR filter and ideal.This paper presents an example of low-pass filter＇s optimized design,and the simulation results show that this method of FIR filter＇s design has a small amount of computation,fast and good performance.