[1]施立恒,余正风,郭亚杰,等.基于局部优化SFLA的VCSEL模型参数识别[J].南京师范大学学报(工程技术版),2018,(04):059.[doi:10.3969/j.issn.1672-1292.2018.04.009]
 Shi Liheng,Yu Zhengfeng,Guo Yajie,et al.Parameter Identification of VCSEL Model Based on Local Optimized SFLA[J].Journal of Nanjing Normal University(Engineering and Technology),2018,(04):059.[doi:10.3969/j.issn.1672-1292.2018.04.009]
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基于局部优化SFLA的VCSEL模型参数识别
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南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2018年04期
页码:
059
栏目:
计算机工程
出版日期:
2018-12-30

文章信息/Info

Title:
Parameter Identification of VCSEL Model Based on Local Optimized SFLA
文章编号:
1672-1292(2018)04-0059-06
作者:
施立恒12余正风12郭亚杰12郭冬梅12曹华琦3
(1.南京师范大学物理科学与技术学院,江苏 南京 210023)(2.南京师范大学江苏省光电技术重点实验室,江苏 南京 210023)(3.南京师范大学商学院,江苏 南京 210023)
Author(s):
Shi Liheng12Yu Zhengfeng12Guo Yajie12Guo Dongmei12Cao Huaqi3
(1.School of Physics and Technology,Nanjing Normal University,Nanjing 210023,China)(2.Jiangsu Key Laboratory on Opto-Electronic Technology,Nanjing Normal University,Nanjing 210023,China)(3.Business School,Nanjing Normal University,Nanjing 210023,China)
关键词:
垂直腔面发射激光器混合蛙跳算法参数识别
Keywords:
VCSELSFLAparameter identification
分类号:
TP248.4
DOI:
10.3969/j.issn.1672-1292.2018.04.009
文献标志码:
A
摘要:
垂直腔面发射激光器(VCSEL)是光纤通信系统的重要光源,精确的参数是光纤通信仿真分析取得正确结果的必要因素. 通过实验测得激光器L-I-V关系和小信号响应,引入混合蛙跳算法(SFLA)来实现参数搜索. 针对经典SFLA收敛速度慢、子群易陷入局部最优的缺点,引入NM单一形状搜索法改进局部搜索方案. 实验结果表明,局部优化SFLA在本工作中收敛速度更快、适应度更优,可准确实现对VCSEL实际参数的识别.
Abstract:
Vertical cavity surface emitting laser(VCSEL)is an important source of optical fiber communication system. The accurate parameters are the key factors to achieve the correct results of optical fiber communication simulation analysis. Based on the experimental results of the relationship between Light-Current-Voltage(L-I-V)characteristics and the small signal response of the laser,we introduce a shuffled frog leaping algorithm(SFLA)to realize the parameter search. In view of the shortcomings of the slow convergence rate of classical SFLA and easiness to fall into local optimal subgroups,the NM single shape search method is introduced to improve the local search scheme. The experimental results show that the local optimization SFLA has faster convergence speed and better adaptability,and that it can accurately identify the actual parameters of VCSEL.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2018-03-30.
基金项目:江苏省高等学校自然科学研究重大项目(17KJA510002).
通讯联系人:郭冬梅,博士,副教授,研究方向:激光精密测量,信号处理. E-mail:guodongmei@njnu.edu.cn
更新日期/Last Update: 2018-12-30