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新奇的半参数算法,用于免干扰调谐吸收光谱气体传感(10)

文章出处:如特安防 人气:发表时间:2018-09-02 18:41:23

Acknowledgments
This work was carried out under a Commission for Technology and Innovation CTI grant (17176.1 PFNM-NM).
europepmc.org
Abbreviations
The following abbreviations are used in this manuscript:
    TDLAS Tunable Diode Laser Absorption Spectroscopy
    FSR Free Spectral Range
    CFT Continuous Fourier Transform
    DFT Discrete Fourier Transform
    RW Rectangular Window
    HWHM Half Width at Half Maximum
    VCSEL Vertical-cavity surface-emitting laser
Appendix A Approximation of the CFT by the Modified DFT
In this paper, the following definition for the continuous Fourier transform (CFT) is used
方程式(A1)
Let us first make some assumptions that will simplify the calculations. Let us assume that the function f(x) is zero outside a certain range (−a/2, a/2) with some a ∈ ℝ and a > 0 and let us indicate with m the number of data points at our disposal. For convenience, m is taken to be even. Let us introduce the sampling rate β as
方程式(A2)
The abscissas of the data xj and kj can be written as:
方程式(A3)
方程式(A4)
with j going from −m/2 to m/2. We can approximate Equation (A1) with a Riemann sum using the fact that f(x) is zero outside the range (−a/2, a/2):
方程式(A5)
where we have approximated the integral with a discrete sum. Clearly, the bigger m is, the better will be the approximation. Now, using Equations (A3) and (A4), we can rewrite (A5) as
方程式(A6)
Author Contributions
F.V. conceived, designed and performed the experiments; U.M. proposed and developed the algorithm; F.V. and U.M. analyzed the data and wrote the paper.
Conflicts of Interest
The authors declare no conflict of interest.
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本文原著:Umberto Michelucci and Francesca Venturini
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    本文标签字:干扰    干扰消除    噪声降低    数字滤波    光谱学    传感器   

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