摘要
FIR数字滤波器优化设计的目标是对滤波器理想性能的逼近。遗传算法是一种模仿生物进化过程的全局优化概率搜索算法,它提出了一种求解复杂系统优化问题的通用框架,且不依赖于问题的领域和种类,在此将自适应的遗传算法应用于FIR数字滤波器的优化设计,通过评价种群的"早熟度"来自适应调整交叉率和变异率,提高了遗传算法的搜索效率。计算机仿真结果证明,该算法能够获得满意的滤波器性能。
The goal of optimized FIR filter design is approaching to the ideal performance of IIR filter. Genetic algorithm is an optimal probability search algorithm, imitating the process of biology evolution, which has proposed an universal method to solve optimized problems of complex system, independent of domain and kind of problems. The proposed algorithm applying self- adaptive genetic algorithm to optimized IIR filter design, and adjusting cross probability and mute probability self- adaptively by evaluating premature convergence degree to improve search efficiency of genetic algorithm. The simulation results demonstrate that the proposed algorithm can achieve satisfying capability of filter.
出处
《现代电子技术》
2010年第2期143-146,共4页
Modern Electronics Technique
关键词
FIR滤波器
优化设计
自适应遗传算法
早熟度
FIR filter
optimized design
self- adaptive genetic algorithm
premature convergence degree
