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电子学报  2014 

基于ELM和MA的微型四频天线设计

DOI: 10.3969/j.issn.0372-2112.2014.09.005, PP. 1693-1698

Keywords: 四频天线,回波损耗,极限学习机,文化基因算法,综合学习粒子群优化算法

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Abstract:

提出一个基于极限学习机ELM(ExtremeLearningMachine)和文化基因算法MA(MemeticAlgorithm)的微型四频(0.92/2.4/3.5/5.8GHz)天线设计算法AntMA-ELM.为了提高天线的性能,算法在MA框架下引入基于综合学习粒子群优化算法CLPSO(ComprehensiveLearningParticleSwarmOptimizer)全局搜索和DSCG(Davies,Swann,andCampeywithGram-schmidt)局部搜索,用于确定天线的几何参数.同时,建立ELM回归模型用于直接评估MA优化的适应值函数.实验结果表明,ELM回归模型能够根据输入参数正确估算天线的回波损耗,使MA算法有效提高设计性能和加速优化过程.天线在四个目标频段的回波损耗值均优于-10dB,满足设计要求.

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