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
Link To Document :
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