GitHub

Solving large systems of linear equations using sparse matrix methods.

Sparse methods are primarily valuable for systems in which the number of non-zero entries is substantially less than the overall size of the matrix. Such situations are common in physical systems, ...
Frontiers

Improving the convergence of an iterative algorithm for solving arbitrary linear equation systems using classical or quantum binary optimization

1 Centro Brasileiro de Pesquisas Físicas, Rio de Janeiro, RJ, Brazil 2 Petróleo Brasileiro S.A., Centro de Pesquisas Leopoldo Miguez de Mello, Rio de Janeiro, Brazil Recent advancements in quantum ...
Scientific Research Publishing

The LA = U Decomposition Method for Solving Systems of Linear Equations ()

1 Department of Environmental Health Science, University of Eswatini, Mbabane, Eswatini. 2 Department of Chemistry, University of Eswatini, Kwaluseni, Eswatini. Systems of linear equations or ...
IEEE

A Discrete-Time Recurrent Neural Network for Solving Rank-Deficient Matrix Equations With an Application to Output Regulation of Linear Systems

Abstract: This paper presents a discrete-time recurrent neural network approach to solving systems of linear equations with two features. First, the system of linear equations may not have a unique ...
GitHub

System of Linear Equations

Multiplies ( A^{-1} ) with ( B ) to obtain the solution vector ( X ). Provides error handling for cases where the matrix ( A ) is not invertible or input is invalid.