Topics in matrix analysis
Accurate singular values of bidiagonal matrices
SIAM Journal on Scientific and Statistical Computing
Matrix computations (3rd ed.)
Component-Based Face Recognition with 3D Morphable Models
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 5 - Volume 05
A tool to improve the execution time of air quality models
Environmental Modelling & Software
Analysing DSGE Models with Global Sensitivity Analysis
Computational Economics
MATH'07 Proceedings of the 12th WSEAS International Conference on Applied Mathematics
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A new and powerful method for matrix decomposition is developed in this work. It is similar to singular value decomposition and the main idea comes from the univariate approximation of a function, given on a planar grid's nodes, by two variable high dimensional model representation. The proposed method is less iteration dependent than the singular value decomposition and the components are determined via straightforward steps containing recursions. It seems to have more capabilities than the singular value decomposition as an alternative method. An illustrative application is also given.