Algorithms to construct/recover low-rank matrices satisfying a set of linear equality constraints have important applications in many signal processing contexts. Recently, theoretical guarantees for ...

Abstract: In this article, the existing approaches, including numerical algorithms as well as neural networks to solve dynamic linear matrix equations, have been presented and reviewed. Specifically, ...

Make sure you are confident in calculating with negative numbers, which is a skill often needed to solve equations. To solve the equation, do the inverse operation. The inverse of multiplying by 12 is ...

In Kronecker products works, matrices are sometimes regarded as vectors and vectors are sometimes made in to matrices. To be precise about these reshaping we use the vector and diagonal extraction ...

This chapter shows how to write linear regression models in matrix form. The purpose is to get you comfortable writing multivariate linear models in different matrix forms before we start working with ...

In this paper, we investigate a system of twelve quaternion matrix equations. Using the real representation of a quaternion matrix, we first derive the least-squares solution with the least norm to ...