Inicio  /  Algorithms  /  Vol: 16 Par: 9 (2023)  /  Artículo
ARTÍCULO
TITULO

Computing the Matrix Logarithm with the Romberg Integration Method

Javier Ibáñez    
José M. Alonso    
Emilio Defez    
Pedro Alonso-Jordá and Jorge Sastre    

Resumen

The matrix logarithm function has applicability in many engineering and science fields. Improvements in its calculation, from the point of view of both accuracy and/or execution time, have a direct impact on these disciplines. This paper describes a new numerical algorithm devoted to matrix logarithm computation and using the Romberg integration method, together with the inverse scaling and squaring technique. This novel method was implemented and compared with three different state-of-the-art codes, all based on Padé approximation. The experimental results, under a heterogeneous matrix test battery, showed that the new method was numerically stable, with an elapsed time midway among the other codes, and it generally offered a higher accuracy.

 Artículos similares

       
 
Carmine Paolino, Alessio Antolini, Francesco Zavalloni, Andrea Lico, Eleonora Franchi Scarselli, Mauro Mangia, Alex Marchioni, Fabio Pareschi, Gianluca Setti, Riccardo Rovatti, Mattia Luigi Torres, Marcella Carissimi and Marco Pasotti    
Analog In-Memory computing (AIMC) is a novel paradigm looking for solutions to prevent the unnecessary transfer of data by distributing computation within memory elements. One such operation is matrix-vector multiplication (MVM), a workhorse of many fiel... ver más

 
Beimbet Daribayev, Aksultan Mukhanbet and Timur Imankulov    
The Poisson equation is a fundamental equation of mathematical physics that describes the potential distribution in static fields. Solving the Poisson equation on a grid is computationally intensive and can be challenging for large grids. In recent years... ver más
Revista: Applied Sciences

 
Aleksandr Cariow, Janusz P. Paplinski and Marta Makowska    
The paper introduces a range of efficient algorithmic solutions for implementing the fundamental filtering operation in convolutional layers of convolutional neural networks on fully parallel hardware. Specifically, these operations involve computing M i... ver más
Revista: Applied Sciences

 
Chang Guo, Demin Li and Xuemin Chen    
Analysis of traffic flow signals plays an important role in traffic prediction and management. As an intrinsic property, the singular point of a traffic flow signal labels a new nonsteady status. Therefore, detecting the singular point is an effective ap... ver más
Revista: Applied Sciences

 
Yang Wang, Jie Liu, Xiaoxiong Zhu, Qingyang Zhang, Shengguo Li and Qinglin Wang    
Structured grid-based sparse matrix-vector multiplication and Gauss?Seidel iterations are very important kernel functions in scientific and engineering computations, both of which are memory intensive and bandwidth-limited. GPDSP is a general purpose dig... ver más
Revista: Applied Sciences