The term "singular value" relates to the distance between a matrix and the set of singular matrices. Eigenvalues play an important role in situations where the matrix is a transformation from one ...

The Arnoldi iteration is two things: the basis of many of the iterative algorithms of numerical linear algebra and, more specifically, a technique for finding eigenvalues of nonhermitian matrices.

Perturbation Bounds for Matrix Eigenvalues contains a unified exposition of spectral variation inequalities for matrices. The text provides a complete and self-contained collection of bounds for the ...

Using eigenvalues (who ever thought you’d use those) to determine the minimum timestep allows the system to remain stable and take multiple smaller steps when needed or just bound the change ...

1. Barbara Brandolini, Francesco Chiacchio, and Jeffrey Langford, Estimates for Sums of Eigenvalues of the Free Plate via the Fourier Transform, Communications in Pure and Applied Analysis, (2020) 19 ...

With data that do not fit the common factor model perfectly, you can expect some of the eigenvalues to be negative. If an iterative factor method converges properly, the sum of the eigenvalues ...

If you specify the COLLINOINT option, the intercept variable is adjusted out first. Then the eigenvalues and eigenvectors are extracted. The analysis in PROC REG is reported with eigenvalues of X'X ...

For [Gunnar]’s diploma thesis, he wanted to build an autonomous bicycle. There’s an obvious problem with this idea, though: how, exactly does a robotic bicycle stand upright? His solution to ...

[11] A.Melman, "Bounds on the extreme eigenvalues of real symmetric Toeplitz matrices", SIAM J. on Matrix Analysis and Applications, 21 (1999), 362-378. [12] A.Melman, "A symmetric algorithm for ...

Jordán, Tibor and Tanigawa, Shin-ichi 2022. Rigidity of Random Subgraphs and Eigenvalues of Stiffness Matrices. SIAM Journal on Discrete Mathematics, Vol. 36, Issue. 3, p. 2367. Micheletti, Andrea and ...