AbstractBy constructing a special similarity transformation matrix, an upper bound for the spectral condition number of a diagonalizable matrix is obtained. This bound can be used in the QR algorithm to estimate the accuracy of the computed eigenvalues
AbstractIn the year 2000 the dominant method for solving matrix eigenvalue problems is still the QR ...
Abstract. For an n n tridiagonal matrix we exploit the structure of its QR factorization to devise ...
In linear algebra, is the canonical forms of a linear transformation. Given a particularly nice basi...
In this article, new upper and lower bounds for the spectral condition number are obtained. These bo...
AbstractIn this note we generalize an upper bound given in Guggenheimer et al. (College Math. J. 26(...
Abstract. Let A be a diagonalizable matrix; so there is an invertible matrix T and a normal matrix D...
Abstract. Let A be a diagonalizable matrix; so there is an invertible matrix T and a normal matrix D...
Perturbation bounds for the relative error in the eigenvalues of diagonalizable and singular matrice...
Exact eigenvalues, eigenvectors, and principal vectors of operators with infinite dimensional ranges...
Perturbation bounds for the relative error in the eigenvalues of diagonalizable and singular matrice...
Perturbation bounds for the relative error in the eigenvalues of diagonalizable and singular matrice...
Perturbation bounds for the relative error in the eigenvalues of diagonalizable and singular matrice...
Perturbation bounds for the relative error in the eigenvalues of diagonalizable and singular matrice...
Abstract. For an n n tridiagonal matrix we exploit the structure of its QR factorization to devise ...
Abstract: Spectral computations of infinite-dimensional operators are notoriously difficult, yet ubi...
AbstractIn the year 2000 the dominant method for solving matrix eigenvalue problems is still the QR ...
Abstract. For an n n tridiagonal matrix we exploit the structure of its QR factorization to devise ...
In linear algebra, is the canonical forms of a linear transformation. Given a particularly nice basi...
In this article, new upper and lower bounds for the spectral condition number are obtained. These bo...
AbstractIn this note we generalize an upper bound given in Guggenheimer et al. (College Math. J. 26(...
Abstract. Let A be a diagonalizable matrix; so there is an invertible matrix T and a normal matrix D...
Abstract. Let A be a diagonalizable matrix; so there is an invertible matrix T and a normal matrix D...
Perturbation bounds for the relative error in the eigenvalues of diagonalizable and singular matrice...
Exact eigenvalues, eigenvectors, and principal vectors of operators with infinite dimensional ranges...
Perturbation bounds for the relative error in the eigenvalues of diagonalizable and singular matrice...
Perturbation bounds for the relative error in the eigenvalues of diagonalizable and singular matrice...
Perturbation bounds for the relative error in the eigenvalues of diagonalizable and singular matrice...
Perturbation bounds for the relative error in the eigenvalues of diagonalizable and singular matrice...
Abstract. For an n n tridiagonal matrix we exploit the structure of its QR factorization to devise ...
Abstract: Spectral computations of infinite-dimensional operators are notoriously difficult, yet ubi...
AbstractIn the year 2000 the dominant method for solving matrix eigenvalue problems is still the QR ...
Abstract. For an n n tridiagonal matrix we exploit the structure of its QR factorization to devise ...
In linear algebra, is the canonical forms of a linear transformation. Given a particularly nice basi...
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