Articles with "matrix inverse" as a keyword



Photo from wikipedia

Material point method simulations using an approximate full mass matrix inverse

Sign Up to like & get
recommendations!
Published in 2021 at "Computer Methods in Applied Mechanics and Engineering"

DOI: 10.1016/j.cma.2021.113667

Abstract: Abstract All material point method (MPM) codes approximate the full mass matrix with a lumped mass matrix. Because this approach causes dissipation, most MPM simulations rely on so-called FLIP methods to limit dissipation. Recent work… read more here.

Keywords: method; mass; mass matrix; full mass ... See more keywords
Photo by tregubov from unsplash

A Matrix-Inverse-Free Implementation of the MU-MIMO WMMSE Beamforming Algorithm

Sign Up to like & get
recommendations!
Published in 2022 at "IEEE Transactions on Signal Processing"

DOI: 10.1109/tsp.2023.3238275

Abstract: The WMMSE beamforming algorithm is a popular approach to address the NP-hard weighted sum rate (WSR) maximization beamforming problem. Although it efficiently finds a local optimum, it requires matrix inverses, eigendecompositions, and bisection searches, operations… read more here.

Keywords: wmmse; beamforming algorithm; implementation; mimo ... See more keywords
Photo by theblowup from unsplash

The generalized orthogonal solutions of the matrix inverse problem AX=B and optimal approximation

Sign Up to like & get
recommendations!
Published in 2017 at "Filomat"

DOI: 10.2298/fil1713023l

Abstract: In this paper, the generalized orthogonal solutions to the matrix inverse problem $AX=B$ and associated optimal approximation problem are considered. The properties and structure of generalized orthogonal matrices are given, the relationships between the generalized orthogonal… read more here.

Keywords: matrix inverse; inverse problem; generalized orthogonal; optimal approximation ... See more keywords
Photo by worldsbetweenlines from unsplash

Computing Generalized Matrix Inverse on Spiking Neural Substrate

Sign Up to like & get
recommendations!
Published in 2018 at "Frontiers in Neuroscience"

DOI: 10.3389/fnins.2018.00115

Abstract: Emerging neural hardware substrates, such as IBM's TrueNorth Neurosynaptic System, can provide an appealing platform for deploying numerical algorithms. For example, a recurrent Hopfield neural network can be used to find the Moore-Penrose generalized inverse… read more here.

Keywords: matrix inverse; generalized matrix; inverse; ibm truenorth ... See more keywords