We study sample covariance matrices of the form $W=(1/n)CC^{\intercal}$, where C is a k × n matrix with independent and identically distributed (i.i.d.) mean 0 ...
The eigenvalue complementarity problem (EiCP) represents a class of mathematical challenges where the determination of eigenvalues and corresponding eigenvectors is constrained by complementarity ...
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 ...
A theorem of U. Grenander and G. Szegö on Toeplitz matrices is generalized. A new method is proposed for investigating eigenvalue distribution of Toeplitz matrices. Journal Information This monthly ...
This article presents a from-scratch C# implementation of the second technique: using SVD to compute eigenvalues and eigenvectors from the standardized source data. If you're not familiar with PCA, ...
If you are looking to develop your skills on vectors or matrices then we can point you in the right direction for some support and practice. The resources below revisit complex Maths topics included ...
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