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 ...
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 ...
ZTEM (Z-Axis Tipper Electromagnetic System) is a frequency-domain airborne electromagnetic exploration method that utilizes natural field sources. This method is highly efficient and capable of ...
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 ...
Abstract: This letter propose a quasi-Newton based weighted minimum mean square error (WMMSE) algorithm without matrix inverse to solve the weighted sum rate (WSR ...
Non-intrusive residential load identification based on load feature matrix and CBAM-BiLSTM algorithm
With the increasing demand for the refined management of residential loads, the study of the non-invasive load monitoring (NILM) technologies has attracted much attention in recent years. This paper ...
Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...
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