基于粒子群算法的状态变量滤波器设计

R. Vural, T. Yıldırım
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引用次数: 15

摘要

粒子群优化算法(Particle Swarm Optimization, PSO)具有概念简单、易于实现和计算效率高等优点,是一种强大的电子电路设计进化计算工具。本文研究了粒子群算法在模拟有源滤波器设计中的应用。为此,在一个二阶状态变量低通有源滤波器的设计上对该算法的性能进行了测试。PSO算法既可以最大限度地减少设计误差,又可以估计与E24或E96系列兼容的组件值。与传统的设计方法相比,PSO实现了更小的设计误差,并在通频带内提供了最大的平坦响应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
State variable filter design using Particle Swarm Optimization
Having the advantage of being very simple in concept, easy to implement and computationally efficient, Particle Swarm Optimization (PSO) algorithm is a powerful evolutionary computation tool for electronic circuit design. In this work, usage of PSO algorithm in analog active filter design is investigated. For this purpose, the performance of the algorithm has been tested on the design of a 2nd order state variable low pass active filter. PSO algorithm both minimizes the design error and estimates the component values that are compatible with either E24 or E96 series. Compared to conventional design procedure, PSO achieved smaller design error and provides a maximally flat response in the pass band.
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