Introduces linear algebra and matrices, with an emphasis on applications, including methods to solve systems of linear algebraic and linear ordinary differential equations. Discusses computational ...

The objectives of this course are: to develop competence in the basic concepts of linear algebra, including systems of linear equations, vector spaces, subspaces, linear transformations, the ...

Random Matrix Theory (RMT) has emerged as an indispensable framework for understanding the statistical properties of matrices whose entries are determined by probabilistic processes. Initially ...

We review several matrix inequalities and give some statistical applications, with special emphasis on canonical correlations; many historical and biographical remarks are also included as well as ...

A new publication from Opto-Electronic Advances; DOI 10.29026/oea.2024.230180, discusses orthogonal matrix of polarization combinations: concept and application to multichannel holographic recording.

AI training time is at a point in an exponential where more throughput isn't going to advance functionality much at all. The underlying problem, problem solving by training, is computationally ...

A relatively obscure eigenvalue due to Wielandt is used to give a simple derivation of the asymptotic distribution of the eigenvalues of a random symmetric matrix. The asymptotic distributions are ...