中国激光, 2018, 45 (1): 0106004, 网络出版: 2018-01-24   

基于SFLA-LSSVM算法的多峰Brillouin散射谱的特征提取 下载: 631次

Feature Extraction of Multi-peak Brillouin Scattering Spectrum Based on SFLA-LSSVM Algorithm
作者单位
燕山大学信息科学与工程学院河北省特种光纤与光纤传感重点实验室, 河北 秦皇岛 066004
摘要
提出了一种利用混合蛙跳算法(SFLA)优化最小二乘支持向量机(LSSVM)算法的混合优化算法, 并将其应用到多峰Brillouin散射谱的特征提取中。SFLA-LSSVM混合优化算法利用SFLA对LSSVM算法中的惩罚因子C和核函数中的核宽度σ进行寻优, 避免了LSSVM算法陷入局部最优导致的Brillouin频移误差较大。通过对相同信噪比、不同线宽以及相同线宽、不同信噪比2种情况下的多峰Brillouin散射谱仿真分析以及实验验证, 拟合适应度为0.0067, 拟合度为99.99%, Brillouin频移误差为0.18 MHz。实验结果表明SFLA-LSSVM混合优化算法能够精确地对多峰Brillouin散射谱进行拟合, 同时该算法具有拟合精度高、均方误差小、运行速度快的特点, 为多峰Brillouin散射谱的特征提取提供了一种新方法。
Abstract
A hybrid optimization algorithm based on shuffled frog leaping algorithm (SFLA) and least squares support vector machine (LSSVM) algorithm is proposed and applied to the feature extraction of multi-peak Brillouin scattering spectra. The penalty factor C and kernel width σ of kernel function in LSSVM algorithm are optimized by SFLA, which reduces the Brillouin frequency shift error caused by the local optimization. Multi-peak Brillouin scattering spectra in the same signal-to-noise with different line width and the same line width with different signal-to-noise ratio are presented by simulation analysis and experimental verification. The fitting fitness of the experimental data is 0.0067, the fitting degree is 99.99%, and the Brillouin frequency shift error is 0.18 MHz. The results show that the SFLA-LSSVM algorithm can precisely fit the multi-peak Brillouin scattering spectrum. The proposed algorithm has the advantages of high fitting precision, small mean square error and fast running speed. The SFLA-LSSVM algorithm is an effective fitting method in the feature extraction of multi-peak Brillouin scattering spectrum.

张燕君, 金培俊, 付兴虎, 张芳草, 侯姣茹, 徐金睿. 基于SFLA-LSSVM算法的多峰Brillouin散射谱的特征提取[J]. 中国激光, 2018, 45(1): 0106004. Zhang Yanjun, Jin Peijun, Fu Xinghu, Zhang Fangcao, Hou Jiaoru, Xu Jinrui. Feature Extraction of Multi-peak Brillouin Scattering Spectrum Based on SFLA-LSSVM Algorithm[J]. Chinese Journal of Lasers, 2018, 45(1): 0106004.

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