基于量子注入的粒子群算法设计数字滤波器

Bipul Luitel, G. Venayagamoorthy
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引用次数: 33

摘要

本文将量子注入粒子群算法(PSO-QI)应用于数字滤波器的设计。在粒子群优化算法中,粒子群优化得到的全局最优粒子(在粒子群星形拓扑中)通过与量子粒子群产生的子代进行比赛来增强,并选择获胜者作为新的全局最优粒子。滤波器的设计基于对理想响应的最佳逼近,通过最小化滤波器响应的通带和阻带的最大波纹。如本文所示,PSO-QI收敛到一个更好的适应度。将该算法应用于有限脉冲响应滤波器和无限脉冲响应滤波器的设计中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Particle Swarm Optimization with Quantum Infusion for the design of digital filters
In this paper, particle swarm optimization with quantum infusion (PSO-QI) has been applied for the design of digital filters. In PSO-QI, Global best (gbest) particle (in PSO star topology) obtained from particle swarm optimization is enhanced by doing a tournament with an offspring produced by quantum behaved PSO, and selecting the winner as the new gbest. Filters are designed based on the best approximation to the ideal response by minimizing the maximum ripples in passband and stopband of the filter response. PSO-QI, as is shown in the paper, converges to a better fitness. This new algorithm is implemented in the design of finite impulse response (FIR) and infinite impulse response (IIR) filter.
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