Displaying 41 – 60 of 164

Showing per page

Convergence of L p -norms of a matrix

Pavel Stavinoha (1985)

Aplikace matematiky

a recurrence relation for computing the L p -norms of an Hermitian matrix is derived and an expression giving approximately the number of eigenvalues which in absolute value are equal to the spectral radius is determined. Using the L p -norms for the approximation of the spectral radius of an Hermitian matrix an a priori and a posteriori bounds for the error are obtained. Some properties of the a posteriori bound are discussed.

Convex SO ( N ) × SO ( n ) -invariant functions and refinements of von Neumann’s inequality

Bernard Dacorogna, Pierre Maréchal (2007)

Annales de la faculté des sciences de Toulouse Mathématiques

A function  f on M N × n ( ) which is SO ( N ) × SO ( n ) -invariant is convex if and only if its restriction to the subspace of diagonal matrices is convex. This results from Von Neumann type inequalities and appeals, in the case where N = n , to the notion of signed singular value.

Directed forests with application to algorithms related to Markov chains

Piotr Pokarowski (1999)

Applicationes Mathematicae

This paper is devoted to computational problems related to Markov chains (MC) on a finite state space. We present formulas and bounds for characteristics of MCs using directed forest expansions given by the Matrix Tree Theorem. These results are applied to analysis of direct methods for solving systems of linear equations, aggregation algorithms for nearly completely decomposable MCs and the Markov chain Monte Carlo procedures.

Currently displaying 41 – 60 of 164