AbstractThe problems of numerical analysis with large sparse matrices often involve a projection of this matrix onto a Krylov subspace to obtain a smaller matrix, which is used to solve the initial problem. The subspace depends on the matrix and on an arbitrary vector. We consider a method to study the sensitivity of the Krylov subspace to a matrix perturbation. This method includes a definition of the condition numbers for the computation of the Krylov basis and the Krylov subspace. A practical method for estimating these numbers is provided. It is based on the solution of a large triangular system
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
AbstractThe problems of numerical analysis with large sparse matrices often involve a projection of ...
AbstractThis paper is devoted to further development of the method studying the condition numbers fo...
International audienceMany problems in scientific computing involving a large sparse square matrix $...
International audienceMany problems in scientific computing involving a large sparse square matrix $...
International audienceMany problems in scientific computing involving a large sparse square matrix $...
Many problems in scientific computing involving a large sparse matrix A are solved by Krylov subspac...
International audienceMany problems in scientific computing involving a large sparse square matrix $...
Many problems in scientific computing involving a large sparse matrix A are solved by Krylov subspac...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
AbstractThe problems of numerical analysis with large sparse matrices often involve a projection of ...
AbstractThis paper is devoted to further development of the method studying the condition numbers fo...
International audienceMany problems in scientific computing involving a large sparse square matrix $...
International audienceMany problems in scientific computing involving a large sparse square matrix $...
International audienceMany problems in scientific computing involving a large sparse square matrix $...
Many problems in scientific computing involving a large sparse matrix A are solved by Krylov subspac...
International audienceMany problems in scientific computing involving a large sparse square matrix $...
Many problems in scientific computing involving a large sparse matrix A are solved by Krylov subspac...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...
Rational Krylov methods are a powerful alternative for computing the product of a function of a larg...