Abschätzung von Normen gewisser Matrizen und eine Anwendung.
Absolute value equations with tensor product structure: Unique solvability and numerical solution
We consider the absolute value equations (AVEs) with a certain tensor product structure. Two aspects of this kind of AVEs are discussed in detail: the solvability and approximate solution. More precisely, first, some sufficient conditions are provided which guarantee the unique solvability of this kind of AVEs. Furthermore, a new iterative method is constructed for solving AVEs and its convergence properties are investigated. The validity of established theoretical results and performance of the...
Absolutely flat idempotents.
Absolutely linear relations.
Absolutely linear relations (Short Communication).
Abstract linear dependence.
Abstract physical traces.
Actions of the symmetric group generated by comparable sets of integers and Smith invariants.
Acyclic digraphs and eigenvalues of -matrices.
Additional results on index splittings for Drazin inverse solutions of singular linear systems.
Additive compound matrices and an inequality for eigenvalues of symmetric stochastic matrices
Additive decomposition of matrices under rank conditions and zero pattern constraints
This paper deals with additive decompositions of a given matrix , where the ranks of the summands are prescribed and meet certain zero pattern requirements. The latter are formulated in terms of directed bipartite graphs.
Additive rank-one nonincreasing maps on Hermitian matrices over the field .
Adhérence d'orbite et invariants.
Adjacency preserving mappings of rectangular matrices.
Adjunctions in Monoidal categories.
Admissible estimators in the general multivariate linear model with respect to inequality restricted parameter set.
Admissible functions and asymptotics for labelled structures by number of components.
Advanced determinant calculus.
Aggregation/disaggregation iterative methods applied to Leontev systems and Markov chains
The paper surveys some recent results on iterative aggregation/disaggregation methods (IAD) for computing stationary probability vectors of stochastic matrices and solutions of Leontev linear systems. A particular attention is paid to fast IAD methods.