نتایج جستجو برای: super additive transformation

تعداد نتایج: 335073  

2016
Jay A. Wood Robert W. Moore JAY A. WOOD

When C ⊆ F is a linear code over a finite field F, every linear Hamming isometry of C to itself is the restriction of a linear Hamming isometry of F to itself, i.e., a monomial transformation. This is no longer the case for additive codes over non-prime fields. Every monomial transformation mapping C to itself is an additive Hamming isometry, but there exist additive Hamming isometries that are...

Journal: :Optics express 2007
E Chorro E Perales D de Fez M J Luque F M Martínez-Verdú

This work uses the S-CIELAB color model to compare images that have been calibrated and processed using a colorimetric dithering method which simulates increments in viewing distance. Firstly, we obtain XYZ calibrated images by applying the appropriate color transformations to the original images. These transformations depend on whether the image is viewed on a display device or encoded by a ca...

2007
P. Filzmoser K. Hron Peter Filzmoser Karel Hron

Outlier detection based on the Mahalanobis distance (MD) requires an appropriate transformation in case of compositional data. For the family of logratio transformations (additive, centered and isometric logratio transformation) it is shown that the MDs based on classical estimates are invariant to these transformations, and that the MDs based on affine equivariant estimators of location and co...

2016
Stan Lipovetsky STAN LIPOVETSKY

The singular value decomposition (SVD) technique is extended to incorporate the additive components for approximation of a rectangular matrix by the outer products of vectors. While dual vectors of the regular SVD can be expressed one via linear transformation of the other, the modified SVD corresponds to the general linear transformation with the additive part. The method obtained can be relat...

Journal: :Proceedings of the American Mathematical Society 1998

1997
O. B. Linton

We consider a nonparametric regression model with a parametric family of dependent variable transformations one of which induces additive covariate eeects. The asymptotic distribution of this regression estimate is given. The practical performance is investigated via an application. 1

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