摘要
基于粒子群优化算法的无源模拟滤波器优化设计方法容易陷入局部最优,收敛速度慢迭代次数多、运算量大且稳定性不够好。提出果蝇优化算法对滤波器的整个参数空间进行高效并行搜索直到获得最优的参数值,实例仿真表明,采用该方法设计的滤波器在相同的带宽准确度及阻带衰减的情况下,具有更快的运算速度及收敛性能。
The optimum design of passive simulation filters based on Particle Swarm Optimization algorithm has slow convergence velocity and may easily fall into local optimum,more iterative times,large computational complexity,and stability is not good enough.A passive analog filter optimization design method is proposed based on the Fruit Fly Optimization Algorithm（FOA）,and it optimizes the circuit＇s parameters in the whole parameters space effectively and globally by FOA until gain the best parameters.The simulation results on the MATLAB show that our algorithm has global convergence and higher speed of optimization.
出处
《湖北第二师范学院学报》
2012年第2期26-29,共4页
Journal of Hubei University of Education
关键词
滤波器
粒子群优化
果蝇优化
filter
Particle Swarm Optimization（PSO）
Fruit Fly Optimization Algorithm
