When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. In October 2024, news broke that Facebook parent company Meta had cracked an "impossible" problem ...

Abstract: This paper presents a novel hardware approach for solving systems of linear equations by leveraging in-memory computing (IMC) with memristive crossbar arrays. Unlike conventional ...

Analog computers are systems that perform computations by manipulating physical quantities such as electrical current, that map math variables, instead of representing information using abstraction ...

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

Department of Mechanical, Chemical and Materials Engineering, University of Cagliari, Piazza d’Armi, 09123 Cagliari, Italy ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

A UNSW Sydney mathematician has discovered a new method to tackle algebra's oldest challenge—solving higher polynomial equations. Polynomials are equations involving a variable raised to powers, such ...

Masaki Kashiwara has won the 2025 Abel prize, sometimes called the Nobel prize of mathematics, for his work on algebraic analysis. Kashiwara, a professor at Kyoto University, Japan, received the award ...

This study introduced an efficient method for solving non-linear equations. Our approach enhances the traditional spectral conjugate gradient parameter, resulting in significant improvements in the ...