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Fourier Analysis of the Aggregation Based Algebraic Multigrid for Stochastic Matrices
We introduce new theoretical results on the convergence of the algebraic multigrid methods for obtaining stationary probability distribution vectors of stochastic matrices. We focus on sparse and nonsymmetric stochastic matrices. Our approach is based on the Fourier transform of the error propagatio...
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Published in: | SIAM journal on matrix analysis and applications 2013-01, Vol.34 (4), p.1596-1610 |
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Main Author: | |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | We introduce new theoretical results on the convergence of the algebraic multigrid methods for obtaining stationary probability distribution vectors of stochastic matrices. We focus on sparse and nonsymmetric stochastic matrices. Our approach is based on the Fourier transform of the error propagation operator. For some special classes of stochastic matrices it allows one to find the optimal parameters of the algorithm and to estimate the rate of convergence. Examples related to the computation of stable gene profiles are presented. [PUBLICATION ABSTRACT] |
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ISSN: | 0895-4798 1095-7162 |
DOI: | 10.1137/130913821 |