Opto-Electronic Engineering, Volume. 37, Issue 8, 42(2010)

The Nonlinearity Correction of Fiber Fabry-Perot Tunable Filter Based on BP Neural Network

ZENG De-hong1,*... RAO Yun-jiang1,2 and RAN Zeng-ling1 |Show fewer author(s)
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  • 1[in Chinese]
  • 2[in Chinese]
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    To rectify the nonlinear relationship between drive voltage and transmission wavelength of the fiber Fabry-Perot tunable filter, a method based on BP neural network was presented. In this method, the drive voltage was input to the BP neural network and the corrected transmission wavelength was got from the output. In order to compare them, linear and quadratic curve fitting method was discussed,too. A set of drive voltage was used as input to the three methods. Compared with the standard value reading from the optical fiber sensor analyzer Si720, the transmission wavelength obtained by the BP neural network has the average error 0.11nm and the maximum error 0.19 nm. In comparison with the other two methods, the average error decreases by 80.6% and 19.7%, and the maximum error decreases by 83.8% and 26.6%, respectively.

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    ZENG De-hong, RAO Yun-jiang, RAN Zeng-ling. The Nonlinearity Correction of Fiber Fabry-Perot Tunable Filter Based on BP Neural Network[J]. Opto-Electronic Engineering, 2010, 37(8): 42

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    Paper Information

    Category:

    Received: Apr. 19, 2010

    Accepted: --

    Published Online: Sep. 7, 2010

    The Author Email: De-hong ZENG (dh_zeng@uestc.edu.cn)

    DOI:

    CSTR:32186.14.

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