A Miniature Four-Band Antenna Design Using ELM and MA

ZENG Qi-ming; JI Zhen; LI Yan; YU Hang

doi:10.3969/j.issn.0372-2112.2014.09.005

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A Miniature Four-Band Antenna Design Using ELM and MA

更新时间：2025-07-16

- A Miniature Four-Band Antenna Design Using ELM and MA
- Acta Electronica Sinica Vol. 42, Issue 9, Pages: 1693-1698(2014)
- 作者机构：
  
  1. 深圳大学信息工程学院,广东,深圳,518060
  2. 深圳大学计算机与软件学院,广东,深圳,518060
  3. 深圳市嵌入式系统设计重点实验室,广东,深圳,518060
  4. 深圳大学信息工程学院,广东,深圳,518060
  5. 深圳大学计算机与软件学院,广东,深圳,518060
  6. 深圳市嵌入式系统设计重点实验室,广东,深圳,518060
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61171125, No.60872125, No.61201042);Shenzhen Special Fund for Overseas High-level Talents Innovation and Entrepreneurship (No.KQC201108300044A);Shenzhen Strategic Emerging Industry Development Special Fund Project (No.JCYJ20120613173154123);National-Guangdong Joint Natural Science Foundation (No.U1201256)
- DOI：10.3969/j.issn.0372-2112.2014.09.005
  CLC： TN822.8
- Published：2014
- 稿件说明：
移动端阅览
ZENG Qi-ming, JI Zhen, LI Yan, et al. A Miniature Four-Band Antenna Design Using ELM and MA[J]. Acta Electronica Sinica, 2014, 42(9): 1693-1698.
DOI：

ZENG Qi-ming, JI Zhen, LI Yan, et al. A Miniature Four-Band Antenna Design Using ELM and MA[J]. Acta Electronica Sinica, 2014, 42(9): 1693-1698. DOI： 10.3969/j.issn.0372-2112.2014.09.005.

摘要

提出一个基于极限学习机ELM（Extreme Learning Machine）和文化基因算法MA（Memetic Algorithm）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（Comprehensive Learning Particle Swarm Optimizer）全局搜索和DSCG（Davies，Swann，and Campey with Gram-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.

Abstract

This paper proposes an extreme learning machine (ELM) and memetic algorithm (MA) based miniature four-band (0.92/2.4/3.5/5.8GHz) antenna design algorithm namely the AntMA-ELM.It combines a comprehensive learning particle swarm optimizer(CLPSO)based global search and a DSCG(Davies

Swann

and Campey with Gram-schmidt) orthogonalization based local search in the MA framework to form a novel optimization algorithm for the geometrical parameters selection of the antenna.An ELM based regression model is introduced to estimate antenna performance

and accelerate the search speed.Experimental results show that the AntMA-ELM obtains promising performance with short computational time.Particularly

the return losses at all targeted frequency bands are smaller than -10dB.

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