Matrices are commonly used in machine learning and data science to represent data and its transformations. In this week, you will learn how matrices naturally arise from systems of equations and how ...

Made by Eduardo Sandalo Porto for the Topics in Object Oriented Programming class; Colégio Técnico de Campinas - Unicamp, 2017; The code is in Portuguese; Compiled using GCC; The program has certain ...

The aim of the following paragraph is to demonstrate that the concept of the stochastic Lyapunov matrix equation is systematically derived from very basic system-theoretical principles, thereby ...

We present a new multiplication concept of quaternion matrices, a new determinant concept, a new inverse concept of quaternion matrix and a new similar matrix concept. Under the new concept system, ...

Because linear systems with ostensible Metzler matrices are not positive, even if their matrix parameters are non-negative, the main limitation to the solution is that the interval estimation only ...

For solving linear systems Ax = b, different preconditioned SOR methods have been proposed by many authors. In this paper, a preconditioned AOR iterative method is presented with a new preconditioner, ...

Researchers are currently working on computational solutions based on quantum systems to accelerate the speed of complex mathematical models. This work presented how to formulate complex computational ...

A comprehensive theory of the matrix linear equation AX + XB = C is presented. The equation is viewed as a vector equation LX = C in the vector space of all m × n matrices. As the main result, two ...