M-M.E.S.S. provides low-rank solvers for large-scale symmetric matrix equations with sparse or sparse + low-rank coefficients. The main focus is on differential and algebraic Riccati equations ...

This project focuses on lossless compression techniques optimizing space, time, and energy for multiplications between binary (or ternary) matrix formats and real-valued vectors.

Matrix decomposition is an area of linear algebra which is focused on expressing a matrix as a product of matrices with prescribed properties. (Photo credit: Merino et al., 2024) Imagine ...

Matrix decomposition is an area of linear algebra which is focused on expressing a matrix as a product of matrices with prescribed properties. (Photo credit: Merino et al., 2024) Imagine discovering ...

Abstract: In this article, the problem of robust sparse beamforming (RSB ... general-rank covariance matrix of the signal of interest (SOI), and multiple statistically independent SOI sources. Finally ...