Eigenvalue problems are a cornerstone of modern applied mathematics, arising in diverse fields from quantum mechanics to structural engineering. At their heart, these problems seek scalar values and ...

SIAM Review contains articles that are written for a wide scientific audience. Articles include expository or survey papers focusing on important advances in applied or computational mathematics, or ...

The eigenvalue complementarity problem (EiCP) represents a class of mathematical challenges where the determination of eigenvalues and corresponding eigenvectors is constrained by complementarity ...

This paper considers the sensitivity of the eigenvalues and eigenvectors of the generalized matrix eigenvalue problem Ax = λ Bx to perturbations of A and B. The ...

Now assume to be symmetric with non-zero off-diagonal elements, i.e. , . Let be the eigenvalues and the normalized eigenvectors of T, i.e. We consider the inverse problem: Determine from and . It is ...

This article presents a from-scratch C# implementation of the second technique: using SVD to compute eigenvalues and eigenvectors from the standardized source data. If you're not familiar with PCA, ...

Network analysis begins with data that describes the set of relationships among the members of a system. The goal of analysis is to obtain from the low-level relational data a higher-level description ...

When a regressor is nearly a linear combination of other regressors in the model, the affected estimates are unstable and have high standard errors. This problem is called collinearity or ...