2012
Approximate multiplication in adaptive wavelet methods
FINĚK, Václav and Dana ČERNÁBasic information
Original name
Approximate multiplication in adaptive wavelet methods
Authors
FINĚK, Václav (203 Czech Republic, belonging to the institution) and Dana ČERNÁ (203 Czech Republic, belonging to the institution)
Edition
CENTRAL EUROPEAN JOURNAL OF MATHEMATICS, 2012, 1895-1074
Other information
Language
English
Type of outcome
Article in a journal
Field of Study
General mathematics
Country of publisher
Poland
Confidentiality degree
is not subject to a state or trade secret
References:
RIV identification code
RIV/46747885:24510/12:#0001005
Organization
Faculty of Science, Humanities and Education – Technical University of Liberec – Repository
UT WoS
316284500014
Keywords in English
Matrix-vector multiplication
Links
GP201/09/P641, research and development project.
Changed: 10/3/2015 13:50, RNDr. Daniel Jakubík
Abstract
V originále
Cohen, Dahmen and DeVore designed in [Adaptive wavelet methods for elliptic operator equations: convergence rates, Math. Comp., 2001, 70(233), 27–75] and [Adaptive wavelet methods IIbeyond the elliptic case, Found. Comput. Math., 2002, 2(3), 203–245] a general concept for solving operator equations. Its essential steps are: transformation of the variational formulation into the well-conditioned infinite-dimensional l 2-problem, finding the convergent iteration process for the l 2-problem and finally using its finite dimensional approximation which works with an inexact right-hand side and approximate matrix-vector multiplication. In our contribution, we pay attention to approximate matrix-vector multiplication which is enabled by an off-diagonal decay of entries of the wavelet stiffness matrices. We propose a more efficient technique which better utilizes actual decay of matrix and vector entries and we also prove that this multiplication algorithm is asymptotically optimal in the sense that storage and number of floating point operations, needed to resolve the problem with desired accuracy, remain proportional to the problem size when the resolution of the discretization is refined.