This chapter is concerned with the so-called \emph{diagonalization problem}. For a given linear operator \(\T\) on a \emph{finite}-dimensional vector space \(\V\), we seek answers to the following ...

The task involves writing a function that accepts a square matrix and returns its eigenvalues and eigenvectors using the NumPy library. It also verifies the equality A * v = λ * v for each eigenvalue ...

This course provides an introduction to linear algebra in Euclidean space. Topics covered include: N-dimensional vectors, dot product, matrices and matrix operations, systems of linear equations and ...

The problem of joint approximate diagonalization of symmetric real matrices is addressed. It is reduced to an optimization problem with the restriction that the matrix of the similarity transformation ...

This course provides an introduction to linear algebra in Euclidean space. Topics covered include: N-dimensional vectors, dot product, matrices and matrix operations, systems of linear equations and ...

Prerequisites: MATH 2331 and MATH 3325, and three additional hours of 3000-4000 level Mathematics. Text(s): Linear Algebra, 5th Edition by Stephen H. Friedberg, Arnold J. Insel, Lawrence E. Spence.

Abstract: We propose a regularized channel diagonalization method for a joint transmit-receive linear optimization in the downlink of a multiuser multiple-input multiple-output (MIMO) communication ...

This course is available on the MSc in Applicable Mathematics, MSc in Operations Research & Analytics and MSc in Quantitative Methods for Risk Management. This course is available as an outside option ...