Understanding and implementation of algorithms to calculate matrix decompositions such as eigenvalue/vector, LU, QR, and SVD decompositions. Applications include data-fitting, image analysis, and ...

This paper takes another look at the convergence analysis of the Arnoldi procedure for solving non-Hermitian eigenvalue problems. Two main viewpoints are put in contrast. The first exploits the ...

Focuses on numerical solution of nonlinear equations, interpolation, methods in numerical integration, numerical solution of linear systems, and matrix eigenvalue problems. Stresses significant ...

This is a preview. Log in through your library . Abstract We review the basic outline of the highly successful diffusion Monte Carlo technique commonly used in contexts ranging from electronic ...

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

This asynchronous online bridge course is specifically designed to help students satisfy the linear algebra admissions requirements for Michigan Tech's Online MS in Applied Statistics, an innovative ...

Math 307 is a theoretical course in linear algebra, geared primarily for students majoring in mathematics, mathematics and physics, and applied mathematics. (Although everyone is welcome, if you're ...