Results 11 to 20 of about 72 (57)

The Sinkhorn-Knopp algorithm: convergence and applications [PDF]

open access: yes, 2006
. As long as a square nonnegative matrix A contains sufficient nonzero elements, then the Sinkhorn-Knopp algorithm can be used to balance the matrix, that is, to find a diagonal scaling of A that is doubly stochastic.
Philip A. Knight, Knight, Philip A.
core   +1 more source

A FAST ALGORITHM FOR MATRIX BALANCING [PDF]

open access: yes, 2007
. As long as a square nonnegative matrix A contains sufficient nonzero elements, then the matrix can be balanced, that is we can find a diagonal scaling of A that is doubly stochastic.
Daniel Ruiz   +3 more
core   +1 more source

Construction of 4 x 4 symmetric stochastic matrices with given spectra

open access: yesOpen Mathematics
The symmetric stochastic inverse eigenvalue problem (SSIEP) asks which lists of real numbers occur as the spectra of symmetric stochastic matrices. When the cardinality of a list is 4, Kaddoura and Mourad provided a sufficient condition for SSIEP by a ...
Jung Jaewon, Kim Donggyun
doaj   +1 more source

Stationary distributions and mean first passage times of perturbed Markov chains

open access: yes, 1992
Stationary distributions of perturbed finite irreducible discrete time Markov chains are intimately connected with the behaviour of associated mean first passage times. This interconnection is explored through the use of generalized matrix inverses. Some
Jeffrey J. Hunter
core  

Linear maps preserving permutation and stochastic matrices

open access: yes, 2008
Let S be the set of n × n (sub)permutation matrices, doubly (sub)stochastic matrices, or the set of m × n column or row (sub)stochastic matrices. We characterize those linear maps T on the linear span of S that satisfy T (S) = S.
Nam-kiu Tsing C   +2 more
core  

Stochastic Complementation, Uncoupling Markov Chains, And The Theory Of Nearly Reducible Systems

open access: yes, 1989
. A concept called stochastic complementation is an idea which occurs naturally, although not always explicitly, in the theory and application of finite Markov chains.
C. D. Meyer
core  

On The Structure of Stochastic Matrices with a Subdominant Eigenvalue Near 1

open access: yes, 1998
An n × n irreducible stochastic matrix P can possess a subdominant eigenvalue, say # 2 (P), near # = 1. In this article we clarify the relationship between the nearness of these eigenvalues and the nearly uncoupling (some authors say "nearly ...
Carl D. Meyer, An N, D. J. Hartfiel
core  

Markov Chain Sensitivity Measured By Mean First Passage Times

open access: yes, 1999
The purpose of this article is to present results concerning the sensitivity of the stationary probabilities for a n-state, time-homogeneous, irreducible Markov chain in terms of the mean first passage times in the chain. Key words.
Grace E. Cho, Carl D. Meyer
core  

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