摘要： 为优化有限脉冲响应(FIR)数字滤波器的设计，提出一种基于双种群的文化算法。种群空间分别按照粒子群优化和差分进化算法独立进化。信仰空间作为知识库，用于保存求解问题的群体经验。仿真实验结果表明，在设计FIR数字滤波器时，该算法具有较高的鲁棒性和较快的收敛速度，优化结果好于同类算法。

关键词: 文化算法, 双种群, 粒子群优化, 差分进化, 有限脉冲响应, 数字滤波器

Abstract: A new cultural algorithm with double populations is proposed for designing Finite Impulse Response(FIR) digital filters. Two populations evolve independently according to Particle Swarm Optimization(PSO) algorithm and Differential Evolution(DE) algorithm respectively. Belief space plays the role of knowledge link in mutual cooperation and promotion between populations. This algorithm provides a new way for the co-evolution technique of multi-population. The computer simulations of FIR filter design indicate that the proposed algorithm is practicable and superior in terms of convergence speed and optimization effect compared with other algorithms.

Key words: Cultural Algorithm(CA), double populations, Particle Swarm Optimization(PSO), Differential Evolution(DE), Finite Impulse Response(FIR), digital filter

中图分类号: 

• TN911.72