Eigenvalue problem phase 1: $\boldsymbol{A}\rightarrow \boldsymbol{H},,\left( \boldsymbol{A}\sim \boldsymbol{H} \right)$, $\boldsymbol{H}$ is a upper Hessenberg ...

The teaching and learning of linear algebra have evolved significantly over recent decades, underpinned by diverse approaches ranging from theoretical expositions to dynamic, model-based environments.

“Mathematics is the art of reducing any problem to linear algebra.” This is a quote often attributed to William Stein, a former mathematics professor at the University of Washington, now the lead ...

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 ...

Implemented Numerical Linear Algebra algorithms with improved performance over the standard algorithm in terms of speed, storage, and stability for special matrices of scientific interest; such as ...

ABSTRACT: We know matrices and their transposes and we also know flip matrices. In my previous paper Matrices-One Review, I introduced transprocal matrix. Flip matrices are transpose of transprocal ...