基于遗传算法的全频带优化FIR低通滤波器设计

Design of full band optimized FIR low pass filter based on genetic algorithm

采用传统遗传算法设计FIR低通滤波器时,仅仅针对FIR低通滤波器的通带或阻带一项性能进行优化,不可避免地会导致另一性能指标的恶化。为了实现对FIR低通滤波器的全频段进行优化,设计了一种新的遗传算法适应度函数,该适应度函数能够将FIR低通滤波器的通带最大波动与阻带最小衰减关联起来;在优化FIR低通滤波器的过程中,能够动态调整通带与阻带的优化平衡,避免了其中任一性能指标的恶化。实验表明,利用该适应度函数优化的FIR低通滤波器在整个频带均能获得较优的性能。

When using traditional genetic algorithm to design filters,the performance optimization of filter pass band or stop band only will inevitably lead to deterioration of another performance index. In order to optimize the entire frequency band of the FIR filter,we propose a new adaptive value function of genetic algorithm, which can associate the maximum fluctuation of pass band with the minimum attenuation of stop band of the FIR filter. In the optimization process,the optimal balance is dynamically adjusted between the pass band and stop band and deterioration of any performance index is avoided.Experiments show that the FIR filter optimized by this fitness function can get better performance in the whole frequency band.