Estimating Extremal Eigenvalues and Condition Numbers of Matrices
Copyright policy )Estimating Extremal Eigenvalues and Condition Numbers of Matrices
A method for estimating the largest (or smallest) eigenvalue of a real positive definite matrix is given. It uses a probabilistic algorithm to compute an estimate which will line within a prescribed distance from the true value. It is a non-iterative method and its execution time can be estimated ''a priori''. This method appears to be especially suitable for the estimation of the condition number of a given matrix.
Numerical computation of eigenvalues and eigenvectors of matrices, positive definite matrix, probabilistic algorithm, estimates, Numerical computation of matrix norms, conditioning, scaling, extremal eigenvalues, condition number
Numerical computation of eigenvalues and eigenvectors of matrices, positive definite matrix, probabilistic algorithm, estimates, Numerical computation of matrix norms, conditioning, scaling, extremal eigenvalues, condition number
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).66 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 1% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!