Chinese Journal of Lasers, Volume. 45, Issue 1, 106004(2018)

Feature Extraction of Multi-peak Brillouin Scattering Spectrum Based on SFLA-LSSVM Algorithm

Zhang Yanjun*, Jin Peijun, Fu Xinghu, Zhang Fangcao, Hou Jiaoru, and Xu Jinrui
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    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.

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    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): 106004

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    Paper Information

    Category: Fiber optics and optical communication

    Received: Jul. 25, 2017

    Accepted: --

    Published Online: Jan. 24, 2018

    The Author Email: Yanjun Zhang (yjzhang@ysu.edu.cn)

    DOI:10.3788/CJL201845.0106004

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