TY - GEN
T1 - Matrix High Dimensional Model Representation (MHDMR) with the weight matrices generated by subspace construction
AU - Tuna, Süha
AU - Demiralp, Metin
PY - 2011
Y1 - 2011
N2 - High Dimensional Model Representation(HDMR) is one of the well-known decomposition methods to partition multivariate functions or given data sets. Although HDMR and its varieties can handle their tasks successfully, it is never revived that it can also be utilized for matrices, function argumented matrices can, until Demiralp and his group has started to work on this topic. After some valuable studies, a new HDMR type has just come forward: Matrix HDMR(MHDMR). In this paper, MHDMR and its features will be introduced.
AB - High Dimensional Model Representation(HDMR) is one of the well-known decomposition methods to partition multivariate functions or given data sets. Although HDMR and its varieties can handle their tasks successfully, it is never revived that it can also be utilized for matrices, function argumented matrices can, until Demiralp and his group has started to work on this topic. After some valuable studies, a new HDMR type has just come forward: Matrix HDMR(MHDMR). In this paper, MHDMR and its features will be introduced.
KW - Decomposition Methods
KW - Fluctuationlessness
KW - Function Valued Matrices
KW - High Dimensional Model Representation
KW - Single Node Fluctuation Free Integration
KW - Subspace Construction
KW - Weight Matrix
UR - http://www.scopus.com/inward/record.url?scp=81855216256&partnerID=8YFLogxK
U2 - 10.1063/1.3637829
DO - 10.1063/1.3637829
M3 - Conference contribution
AN - SCOPUS:81855216256
SN - 9780735409569
T3 - AIP Conference Proceedings
SP - 1192
EP - 1195
BT - Numerical Analysis and Applied Mathematics, ICNAAM 2011 - International Conference on Numerical Analysis and Applied Mathematics
T2 - International Conference on Numerical Analysis and Applied Mathematics: Numerical Analysis and Applied Mathematics, ICNAAM 2011
Y2 - 19 September 2011 through 25 September 2011
ER -