Geodesic
Deconvolution of optical spectra distorted by random noise using an artificial immune system
Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki, Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, Tome 160 (2018) no. 1, pp. 72-80 Cet article a éte moissonné depuis la source Math-Net.Ru

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The deconvolution of a complex spectral contour into components by the algorithm of artificial immune system has been considered. It is the optimization method which is based on the behavior of the immune system. The random fractal noise has been used as a noise model which allows one to employ different noises, such as the high- and low-frequency noises. The results of the decomposition of the model contour consisting of three Gaussian components have been represented. The dependence of the efficiency of decomposition of spectral contours on the relative level of noise and the spectral structure of noise has been investigated.
Keywords: optical spectroscopy, artificial immune system, random noise.
Mots-clés : deconvolution of complex spectra 
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     title = {Deconvolution of optical spectra distorted by random noise using an artificial immune system},
     journal = {U\v{c}\"enye zapiski Kazanskogo universiteta. Seri\^a Fiziko-matemati\v{c}eskie nauki},
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     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/UZKU_2018_160_1_a6/}
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D. I. Galiakhmetova; M. E. Sibgatullin; D. Z. Galimullin; D. I. Kamalova. Deconvolution of optical spectra distorted by random noise using an artificial immune system. Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki, Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, Tome 160 (2018) no. 1, pp. 72-80. http://geodesic.mathdoc.fr/item/UZKU_2018_160_1_a6/

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