Paper Info
Title
Substructuring, dimension reduction and applications: an introduction
Abstract
There are a variety of reasons to go for substructuring and dimension reduction in scientific computations and applications. Substructuring makes it possible to solve large and seemingly intractable computational problems solvable in today technology by some kind of Divide-and-Conquer technique; Substructuring offers a general methodology to do parallelization; And substructuring allows one to design algorithms to preserve substructures at a very fine level of underlying problems of interest, which usually go unnoticed by more general purposed methods. Often if done right, payoff will be significant. Dimension reduction is a rather broader concept referring to techniques that achieve significant reductions of problem sizes so as to make intractable numerical simulations tractable. Successful examples are abundant, including reduced order modelling from dynamical systems and circuit design, cluster text data analysis, and data mining. This minisymposium presents currently active researches in substructuring strategies, model reduction and applications, and domain decompositions, among others.
Year
DOI
Venue
2004
10.1007/11558958_31
PARA
Keywords
Field
DocType
data mining,general purposed method,dimension reduction,circuit design,significant reduction,substructuring strategy,general methodology,model reduction,intractable computational problems solvable,cluster text data analysis,dynamic system,data analysis,scientific computing,domain decomposition,divide and conquer,numerical simulation
Computational problem,Dimensionality reduction,Parallel algorithm,Computer science,Circuit design,Theoretical computer science,Dynamical systems theory,Computation,Stochastic game,Distributed computing
Conference
Volume
ISSN
ISBN
3732
0302-9743
3-540-29067-2
Citations 
PageRank 
References 
0
0.34
1
Authors
2
Name
Order
Citations
PageRank
Zhaojun Bai1661107.69
Ren-Cang Li227850.05