Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9507164 | Applied Mathematics and Computation | 2005 | 19 Pages |
Abstract
When the values of a multivariate function f(x1, â¦, xN), having N independent variables like x1, â¦, xN are given at the nodes of a cartesian product set in the space of the independent variables and an interpolation problem is defined to find out the analytical structure of this function some difficulties arise in the standard methods due to the multidimensionality of the problem. Here, the main purpose is to partition this multivariate data into low-variate data and to obtain the analytical structure of the multivariate function by using this partitioned data. High dimensional model representation (HDMR) is used for these types of problems. However, if HDMR requires all components, which means 2N number of components, to get a desired accuracy then factorized high dimensional model representation (FHDMR) can be used. This method uses the components of HDMR. This representation is needed when the sought multivariate function has a multiplicative nature. In this work we introduce how to utilize FHDMR for these problems and present illustrative examples.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
M. Alper Tunga, Metin Demiralp,