Synthesis of cross-coupled resonator filters using comprehensive learning particle swarm optimization (CLPSO) algorithm

A. Azad, D. Jhariya, A. Mohan
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引用次数: 4

Abstract

This paper presents the synthesis of coupling matrix of cross-coupled resonator filters using comprehensive learning particle swarm optimization (CLPSO) algorithm. The CLPSO algorithm does not require gradient information of the fitness function under consideration. The coupling topology of the filter is incorporated in the optimization process to eliminate the need of similarity transformations of the coupling matrix. The CLPSO algorithm is applied to synthesize third- and fourth-order cross-coupled resonator filters.
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基于综合学习粒子群优化(CLPSO)算法的交叉耦合谐振滤波器合成
提出了一种基于综合学习粒子群优化(CLPSO)算法的交叉耦合谐振滤波器耦合矩阵的合成方法。CLPSO算法不需要考虑适应度函数的梯度信息。在优化过程中引入滤波器的耦合拓扑结构,消除了对耦合矩阵进行相似变换的需要。将CLPSO算法应用于三阶和四阶交叉耦合谐振滤波器的合成。
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