Abstract: The effective solution of system of nonlinear equations (SNEs) is crucial for the creation of engineering and scientific models. SNEs can be represented and analyzed as an optimization ...

The new analogue in-memory chip performs computation inside memory, lowering power consumption and latency for AI and ...

A new chip aims to dramatically reduce energy consumption while accelerating the processing of large amounts of data.

The world today is marked by paradox. Never before has humanity possessed such extraordinary scientific knowledge, ...

Indian-origin mathematician Nalini Joshi has been named New South Wales Scientist of the Year, becoming the first mathematician to receive the honour for her groundbreaking contributions to applied ...

NonlinearSystems.jl is a Julia package for solving nonlinear systems of equations and nonlinear least squares. It renovates well-trusted solution algorithms with highly performant and extensible ...

Nonlinear problems, originating from applied science that is closely related to practices, contain rich and extensive content. It makes the corresponding nonlinear models also complex and diverse. Due ...

Abstract: Riccati matrix equation (RME), a critical nonlinear matrix equation in autonomous driving and deep learning. However, memory-compute separation in traditional solving systems leads to ...

Scientists have discovered a way to use live tissue as a computational reservoir to solve problems and potentially predict chaotic systems like the weather. When you purchase through links on our site ...

Neural networks have been widely used to solve partial differential equations (PDEs) in different fields, such as biology, physics, and materials science. Although current research focuses on PDEs ...

As capable as artificial intelligence (AI) deep learning algorithms have become, the human brain still vastly outperforms silicon-based neural networks when it comes to energy efficiency. In efforts ...