The traditional way of finding minimum eigenvalue of a hermitian matrix consists of Semi-Classical method where we use Classical Optimization and variational principles to find the lowest eigenvalue ...

This project uses the dataset of pictures of peoples faces with different lighting know as Yale Faces and creates correlation matrices, performs eigenvector analysis, and applies single value ...

Abstract Let A be an n × n Hermitian matrix and A = UΛUH be its spectral decomposition, where U is a unitary matrix of order n and Λ is a diagonal matrix. In this note we present the perturbation ...

Deep neural networks (DNNs) have achieved remarkable success across various fields, including computer vision, natural language processing, and speech recognition. This success is largely attributed ...

Abstract: This paper introduces a method based on generating matrices for obtaining trigonometric number transform (TNT) eigenvectors. We show how to construct such matrices and explain how to use ...