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dc.contributor.authorBektaş S.
dc.contributor.authorŞişman Y.
dc.date.accessioned2020-06-21T09:27:29Z
dc.date.available2020-06-21T09:27:29Z
dc.date.issued2010
dc.identifier.issn1992-1950
dc.identifier.urihttps://hdl.handle.net/20.500.12712/4069
dc.description.abstractL2-norm, also known as the least squares method was widely used in the adjustment calculus. The weaknesses of the least squares method were the effect of gross measurements error on the solution and the disturbance and absorbance of gross error on the solution. L1-norm, also known as the least absolute values method, was affected by almost none or very little from gross error. Therefore L1-norm method, used for parameters estimation in some special case, has been successfully used for outlier measurements detection. In this study, the L1 and L2-norm adjustment methods have been taken relatively to each other's advantages and disadvantages and the numerical application of the two-dimensional similarity coordinate transformation were made and the results of both methods are discussed. © 2010 Academic Journals.en_US
dc.language.isoengen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGross errorsen_US
dc.subjectL1 and L2-normen_US
dc.subjectOutlier detectionen_US
dc.subjectSimilarity transformationen_US
dc.titleThe comparison of L11 and L22-norm minimization methodsen_US
dc.typearticleen_US
dc.contributor.departmentOMÜen_US
dc.identifier.volume5en_US
dc.identifier.issue11en_US
dc.identifier.startpage1721en_US
dc.identifier.endpage1727en_US
dc.relation.journalInternational Journal of Physical Sciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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