Welcome to the nlp-2.1-matrix-decomposition repository! This project provides a collection of algorithms for matrix decomposition, a fundamental concept in linear algebra. Whether you're working on ...

Currently, eig and similar throw no method eigfact when applied to these types of matrices. We should be able to provide efficient LAPACK-based solvers for these types. For Tridiagonal, we can exploit ...

Abstract: The implicitly restarted Arnoldi method (IRAM), which relies on Krylov subspace iteration, is an effective approach for extracting desired partial eigenpairs in characteristic mode analysis ...

The constrained least-squares n × n-matrix problem where the feasibility set is the subspace of the Toeplitz matrices is analyzed. The general, the upper and lower triangular cases are solved by ...

Parallel computing continues to advance, addressing the demands of high-performance tasks such as deep learning, scientific simulations, and data-intensive computations. A fundamental operation within ...