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State variable filter design using Particle Swarm Optimization

机译:状态可变过滤器设计使用粒子群优化

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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.
机译:具有非常简单的概念的优势,易于实现和计算高效,粒子群优化(PSO)算法是电子电路设计的强大进化计算工具。在这项工作中,研究了模拟有源滤波器设计中PSO算法的使用。为此目的,算法的性能已经在2 nd 订单状态变量低通有源滤波器的设计上进行了测试。 PSO算法均可最大限度地减少设计错误,并估计与E24或E96系列兼容的组件值。与传统设计过程相比,PSO实现了较小的设计误差,并在通带中提供最大平坦的响应。

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