Mehrdoust, Farshid A randomized algorithm for estimating the condition number of matrices. (English) Zbl 1299.65088 Math. Rep., Bucur. 15(65), No. 3, 203-210 (2013). Many algorithms use singular value decomposition or Lanczos methods to find the condition number of a matrix. The author presents a linear time quasi-Monte Carlo algorithm to estimate the condition number of large matrices by the computation of eigenvalues. The efficiency of the algorithm is illustrated by some numerical results. Reviewer: Hang Lau (Montreal) Cited in 1 Document MSC: 65F35 Numerical computation of matrix norms, conditioning, scaling 65C05 Monte Carlo methods 65C40 Numerical analysis or methods applied to Markov chains 15A12 Conditioning of matrices 65F15 Numerical computation of eigenvalues and eigenvectors of matrices Keywords:randomized algorithm; quasi-Monte Carlo method; Markov chain; condition number; large matrices; eigenvalues; numerical results PDFBibTeX XMLCite \textit{F. Mehrdoust}, Math. Rep., Buchar. 15(65), No. 3, 203--210 (2013; Zbl 1299.65088)