• DocumentCode
    3721300
  • Title

    Parametric spectral signal restoration via maximum entropy constraint and its application

  • Author

    Hai Liu;Zhaoli Zhang;Sanya Liu;Jiangbo Shu;Tingting Liu

  • Author_Institution
    National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, 430079, China
  • fYear
    2015
  • Firstpage
    353
  • Lastpage
    357
  • Abstract
    In this paper, we will propose a new framework which can estimate the desired signal and the instrument response function (IRF) simultaneously from the degraded spectral signal. Firstly, the spectral signal is considered as a distribution, thus, new entropy (called differential-entropy, DE) is defined to measure the distribution with a uniform distribution, which allows negative value existing. Moreover, the IRF is parametrically modeled as a Lorentzian function. Comparative results manifest that the proposed method outperforms the conventional methods on peak narrowing and noise suppression. The deconvolution IR spectrum is more convenient for extracting the spectral feature and interpreting the unknown chemical mixtures.
  • Keywords
    "Kernel","Entropy","Signal processing","Deconvolution","Noise level","Convergence","Conferences"
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Signal Processing Education Workshop (SP/SPE), 2015 IEEE
  • Type

    conf

  • DOI
    10.1109/DSP-SPE.2015.7369579
  • Filename
    7369579