IEEE

Techniques for Generating Analytic Covariance Expressions for Eigenvalues and Eigenvectors

Abstract: One of the key problems in data fusion is the estimation of a parameter vector from a set of noisy measurements. In many cases, the optimal estimate of such a parameter vector can be solved ...
acm.org

Solution of Eigenvalue problems with approximately known Eigenvectors

It is often desired to solve eigenvalue problems of the type (A - &lgr;1)C = 0 or (A - &lgr;B)C = 0 repeatedly for similar values of the matrix elements Aij, where A and B are Hermitean or real ...
GitHub

"Only link once" sometimes proposes candidates for already linked terms

All three terms already have real links. Not sure why eigenvalue is proposed for linking twice and vector once. I have selected the option to "Only link once". The ...
Visual Studio Magazine

Principal Component Analysis from Scratch Using Singular Value Decomposition with C#

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, ...
Visual Studio Magazine

Principal Component Analysis (PCA) from Scratch Using the Classical Technique with C#

Transforming a dataset into one with fewer columns is more complicated than it might seem, explains Dr. James McCaffrey of Microsoft Research in this full-code, step-by-step machine learning tutorial.
IEEE

Eigenvalue Decomposition of a Parahermitian Matrix: Extraction of Analytic Eigenvectors

Abstract: An analytic parahermitian matrix admits in almost all cases an eigenvalue decomposition (EVD) with analytic eigenvalues and eigenvectors. We have previously defined a discrete Fourier ...