@inproceedings{cc01345c393f4fef8acd45d2b7c36d48,
title = "Fundamental elements of vector enhanced multivariance product representation",
abstract = "A new version of High Dimensional Model Representation (HDMR) is presented in this work. Vector HDMR has been quite recently developed to deal with the decomposition of vector valued multivariate functions. It was an extension from scalars to vectors by possibly using matrix weights. However, that expansion is based on an ascending multivariance starting from a constant term via a set of appropriately imposed conditions which can be related to orthogonality in a conveniently chosen Hilbert space. This work adds more flexibility by introducing certain matrix valued univariate support functions. We assume weight matrices proportional to unit matrices. This work covers only the basic issues related to the fundamental elements of the new approach.",
keywords = "Approximation, Enhanced Multivariance Product Representation, High Dimensional Model Representation, Matrix Theory, Multidimensional Problems",
author = "Berfin Kalay and Metin Demiralp",
year = "2012",
doi = "10.1063/1.4756580",
language = "English",
isbn = "9780735410916",
series = "AIP Conference Proceedings",
number = "1",
pages = "1998--2001",
booktitle = "Numerical Analysis and Applied Mathematics, ICNAAM 2012 - International Conference of Numerical Analysis and Applied Mathematics",
edition = "1",
note = "International Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2012 ; Conference date: 19-09-2012 Through 25-09-2012",
}