Displaying similar documents to “Asynchronous weighted additive Schwarz methods.”

The limit of inconsistency reduction in pairwise comparisons

Waldemar W. Koczkodaj, Jacek Szybowski (2016)

International Journal of Applied Mathematics and Computer Science

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This study provides a proof that the limit of a distance-based inconsistency reduction process is a matrix induced by the vector of geometric means of rows when a distance-based inconsistent pairwise comparisons matrix is transformed into a consistent PC matrix by stepwise inconsistency reduction in triads. The distance-based inconsistency indicator was defined by Koczkodaj (1993) for pairwise comparisons. Its convergence was analyzed in 1996 (regretfully, with an incomplete proof) and...

The problem of kings.

Larsen, Michael (1995)

The Electronic Journal of Combinatorics [electronic only]

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Inversion of square matrices in processors with limited calculation abillities

Krzysztof Janiszowski (2003)

International Journal of Applied Mathematics and Computer Science

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An iterative inversion algorithm for a class of square matrices is derived and tested. The inverted matrix can be defined over both real and complex fields. This algorithm is based only on the operations of addition and multiplication. The numerics of the algorithm can cope with a short number representation and therefore can be very useful in the case of processors with limited possibilities, like different neuro-computers and accelerator cards. The quality of inversion can be traced...

On the matrix form of Kronecker lemma

João Lita da Silva, António Manuel Oliveira (2009)

Discussiones Mathematicae Probability and Statistics

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A matrix generalization of Kronecker's lemma is presented with assumptions that make it possible not only the unboundedness of the condition number considered by Anderson and Moore (1976) but also other sequences of real matrices, not necessarily monotone increasing, symmetric and nonnegative definite. A useful matrix decomposition and a well-known equivalent result about convergent series are used in this generalization.