M.Sc. in Applied Mathematics, Technion (Israel Institute of Technology) Ph.D. in Applied Mathematics, Caltech (California Institute of Technology) [1] A. Melman (2023): “Matrices whose eigenvalues are ...

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 ...

Nonnegative Matrix Factorization (NMF) has emerged as a powerful tool in data analysis, particularly noted for its ability to produce parts‐based, interpretable representations from high-dimensional ...

It is shown that a class of infinite, block-partitioned, stochastic matrices has a matrix-geometric invariant probability vector of the form (x0,x1,...), where xk=x0Rk, for k≥ 0. The rate matrix R is ...

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.

This is a preview. Log in through your library . Abstract Indefinite approximations of positive semidefinite matrices arise in various data analysis applications involving covariance matrices and ...