Abstract: Sparse Bayesian learning (SBL) is an advanced statistical framework that dominantly enhances the sparse features of targets of interest in radar imagery. A widely adopted strategy for ...

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

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 ...

One of the ironies of the moment we’re in is that this inversion of good and evil, truth and falsehood has become more widespread and extreme at the very time that science, technology, and ...

Inversion Space’s demonstration reentry capsule before its launch on the SpaceX Transporter-12 rideshare. Credit: Inversion Space WASHINGTON — Startup Inversion Space says its first flight of a ...

Matrix factorization techniques, such as principal component analysis (PCA) and independent component analysis (ICA), are widely used to extract geological processes from geochemical data. However, ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The development of low-loss reconfigurable integrated optical devices enables further ...

CHICAGO--(BUSINESS WIRE)--Matrix Executions, an agency-only broker dealer and trading technology provider, has enhanced its US listed options algorithm technology suite with new price discovery and ...

The stochastic inversion method using logging data as conditional data and seismic data as constraint data has a higher vertical resolution than the conventional deterministic inversion method.

This week I interviewed Senator Amy Klobuchar, Democrat of Minnesota, about her Preventing Algorithmic Collusion Act. If you don’t know what algorithmic collusion is, it’s time to get educated, ...