基于ELM和MA的微型四频天线设计

doi:10.3969/j.issn.0372-2112.2014.09.005

电子学报 ›› 2014, Vol. 42 ›› Issue (9): 1693-1698.DOI: 10.3969/j.issn.0372-2112.2014.09.005

基于ELM和MA的微型四频天线设计

曾启明^1,3, 纪震³, 李琰^2,3, 俞航^2,3

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

收稿日期:2013-09-06 修回日期:2014-01-08 出版日期:2014-09-25
- 作者简介:
- 曾启明 男，1984年4月生于广东省清远市，现为深圳大学信息工程学院信号与信息处理专业硕博连读研究生.研究方向为数字射频通信. E-mail：zengqm@szu.edu.cn；纪震 男，1973年8月生于江苏省溧阳市，1999年毕业于西安交通大学，博士学位，2004年晋升为教授.主要研究方向包括智能信号处理、嵌入式系统、生物医学工程. E-mail：jizhen@szu.edu.cn；李琰 男，1978年生，2007年毕业于法国巴黎第十一大学，博士学位.2008年进入深圳大学，研究方向是混合信号集成电路设计. E-mail：liyan@szu.edu.cn；俞航 男，1977年生于北京市，2010 年于佛罗里达大学获得博士学位，现就职于深圳大学.研究方向包括低功耗射频/模拟/混合集成电路设计、生物医学相关的微系统设计、通讯天线的小型化设计等. E-mail：yuhang@szu.edu.cn
- 基金资助:
- 国家自然科学基金 (No.61171125，No.60872125，No.61201042）; 深圳市海外高层次人才创新创业专项资金 (No.KQC201108300044A）; 深圳市战略性新兴产业发展专项资金项目 (No.JCYJ20120613173154123）; 国家-广东省联合自然科学基金 (No.U1201256）

A Miniature Four-Band Antenna Design Using ELM and MA

ZENG Qi-ming^1,3, JI Zhen³, LI Yan^2,3, YU Hang^2,3

1. College of Engineering and Information, Shenzhen University, Shenzhen, Guangdong 518060, China;
2. College of Computer Science and Software Emgineering, Shenzhen University, Shenzhen, Guangdong 518060, China;
3. Shenzhen Key Laboratory of Embedded System Design, Shenzhen, Guangdong 518060, China

Received:2013-09-06 Revised:2014-01-08 Online:2014-09-25 Published:2014-09-25
- Supported by:
- 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)

摘要/Abstract

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.

关键词: 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

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.

Key words: four-band antenna, return loss, extreme learning machine, memetic algorithm, CLPSO

中图分类号:

TN822.8

曾启明, 纪震, 李琰, 等. 基于ELM和MA的微型四频天线设计[J]. 电子学报, 2014, 42(9): 1693-1698.

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.

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基于ELM和MA的微型四频天线设计

A Miniature Four-Band Antenna Design Using ELM and MA

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