2013
DOI: 10.1364/jot.80.000444
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Construction of adaptive spectral analyzers on the basis of acousto-optic spectrometers

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Cited by 5 publications
(2 citation statements)
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“…This makes it possible to drastically reduce the registration time required to perform the task of distinguishing (recognizing) data. The reduction is the ratio of the total number of recorded spectral channels of the device to the number of informative channels (N gen /N inf ) and can reach 2-x for typical AO filters by orders [8]. This approach is especially effective in the analysis of line spectra with a high degree of sparseness (sparse spectra), which is typical, for example, for gas analysis problems [9,10].…”
Section: Introductionmentioning
confidence: 99%
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“…This makes it possible to drastically reduce the registration time required to perform the task of distinguishing (recognizing) data. The reduction is the ratio of the total number of recorded spectral channels of the device to the number of informative channels (N gen /N inf ) and can reach 2-x for typical AO filters by orders [8]. This approach is especially effective in the analysis of line spectra with a high degree of sparseness (sparse spectra), which is typical, for example, for gas analysis problems [9,10].…”
Section: Introductionmentioning
confidence: 99%
“…Some modern AO filters implement new functions, such as spectral window width control or spectral filtering multiwindow mode [13], which could also be used to increase contrast, but these possibilities are not considered in this work. The idea of selective spectral registration, also called fragmentary spectral registration [10], is described in general terms [14] and was analyzed either under special assumptions [12] , or without registration of spatial distributions in the papers [8,10]. Thus, it is of interest to determine the approach to the optimal choice of a limited number of zones (lines) for recording the spectra of various objects for problems of contrast " visualization" of objects against various backgrounds.…”
Section: Introductionmentioning
confidence: 99%