Improving linearity of position-sensitive detector using support vector machines

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摘要 Anintelligentmethodforimprovingpositionlinearityofposition-sensitivedetector(PSD),basedonsupportvectormachines(SVMs),isdeveloped.TheSVMisestablishedbasedonthestructuralriskminimizationprincipleratherthanminimizingtheempiricalerrorcommonlyimplementedinneuralnetworks.SVMcanachievehighergeneralizationperformance.TrainingSVMisequivalenttosolvingalinearlyconstrainedquadraticprogrammingproblem,thusthesolutionofSVMisalwaysuniqueandgloballyoptimal.Theimprovingpositionlinearityprocedurehasbeenillustratedusingatwo-dimensional(2D)PSD.ItispointedoutthatthepositionlinearityofthemeasuringsystemwithaproperSVMcorrectionisimprovedbytwoordersofmagnitudeinthemeasurementrange.
机构地区 不详
出版日期 2005年04月14日(中国期刊网平台首次上网日期,不代表论文的发表时间)
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