1996
DOI: 10.1016/0003-2670(96)00204-8
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Comparison of optimization algorithms for piecewise linear discriminant analysis: application to Fourier transform infrared remote sensing measurements

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Cited by 12 publications
(8 citation statements)
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“…The PLDA method 5,6,[9][10][11][12][13][14]28 was then applied to the training patterns to compute the classifier. This is a mathematical technique used to form multiple linear boundaries or surfaces called discriminants within the data space.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The PLDA method 5,6,[9][10][11][12][13][14]28 was then applied to the training patterns to compute the classifier. This is a mathematical technique used to form multiple linear boundaries or surfaces called discriminants within the data space.…”
Section: Resultsmentioning
confidence: 99%
“…With these data, classifiers can be developed that enable the analyst to identify the presence of target species within an image. Piecewise linear discriminant analysis [9][10][11][12][13][14] (PLDA) is used to generate classifiers based on training sets composed of simulated analyte-active data and randomly picked analyte-inactive measurements from background images. These classifiers are subsequently tested with field-collected imaging data with either ethanol or methanol as the target analyte.…”
Section: Introductionmentioning
confidence: 99%
“…Fifty interferogram s were collected for each of these three con gurations. This procedure was repeated at each step as the blackbody temperature was lowered to 45,40,35,30,29,28,27,26,25,24,23,22,21,20,15,10, and 5 8C. The data collection was then completed by raising the temperature to two nal settings of either 25.5/50, 18/32, 18/31, 24.5/25.5, or 18/50 8C.…”
Section: Methodsmentioning
confidence: 99%
“…In the work described here, the patterns in the active data class are generated synthetically from the modulation of a single laboratory-collected spectrum. [44][45][46][47][48] These spectra are then overlaid with backgrounds collected from a broad range of locations around the nation, in order to simulate any theoretical scenario the ASPECT program may encounter from high to low intensity sources. This collection of synthetic active spectra is supplemented by a second set of inactive spectra drawn from a separate pool of backgrounds collected from multiple vetted locations.…”
Section: Referencesmentioning
confidence: 99%
“…Once computed, the classification model is applicable to other sets of data processed in the same fashion, assuming the target analyte remains the same. [44][45][46][47][48] The specifics of the implementation of PLDA for the thesis work will be described section 3.4.…”
Section: Introductionmentioning
confidence: 99%