Abstract: Recently, analog matrix inversion circuits (INV) have demonstrated significant advantages in solving matrix equations. However, solving large-scale sparse tridiagonal linear systems (TLS) ...

Abstract: In this article, the existing approaches, including numerical algorithms as well as neural networks to solve dynamic linear matrix equations, have been presented and reviewed. Specifically, ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this work, we describe the development of a new algorithm for the computation of ...

Computator.NET is a special kind of numerical software that is fast and easy to use but not worse than others feature-wise. It's features include: - Real and complex functions charts - Real and ...

This Project is based on the Galerkin method of solving differencial equations. A weak formulation of the Schrodinger equation is used with a set of basis functions to break the continuous ...

A matrix is a rectangular array of numbers, symbols, or expressions arranged in rows and columns. They are a crucial part of linear algebra and have various applications in fields like engineering, ...

Quantum computing (QC) has advantages of speed and storage over classical computing, but it is based on a linear paradigm. However, many problems of interest are nonlinear. A viable QC algorithm ...