基于杂交粒子群算法的FIR数字滤波器设计

FIR digital filter design based on crossbreeding particle swarm optimization algorithm

介绍了杂交粒子群算法的原理,通过三个典型Benchmark函数对该算法的收敛精度进行了测试。将杂交粒子群算法应用到FIR数字滤波器的设计中,从而计算出FIR数字滤波器的系数。通过高通和带通两个实例进行仿真实验,并与Parks-McClellan算法设计的滤波器进行对比,结果表明,采用杂交粒子群算法设计FIR数字滤波器具有更好的通带和阻带特性,是一种有效的方法。

Crossbreeding particle swarm optimization algorithm is described. The algorithm is tested by three typical Benchmark function and shows that it has better convergence accuracy. It uses this algorithm to design FIR digital filter, and calculates the coefficients of FIR digital filter. By experiments on high-pass and band-pass FIR digital filters, compared with Parks-McClellan, it shows that, crossbreeding particle swarm optimization algorithm is superior to Parks-McClellan, and the effectiveness of algorithm is also demonstrated.