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Computation of Eigenvectors and Eigenvalues and the Singular Value Decomposition

1998
Before we discuss methods for computing eigenvalues, we mention an interesting observation. Consider the polynomial, f(& λ), $$ {{\lambda }^{p}} + {{a}_{{p - 1}}}{{\lambda }^{{p - 1}}} + ... + {{a}_{1}}\lambda + {{a}_{0}} $$ Now form the matrix, A, $$ \left[ \begin{gathered} 0 1 0 ... 0 \hfill \\ 0 0 1 ... 0 \hfill \\ \ddots \hfill \\ 0 0 0 .
openaire   +1 more source

Nondegeneracy of eigenvectors and singular vector tuples of tensors

Science China Mathematics, 2022
Shenglong Hu
exaly  

Singular Value Decomposition of a Matrix Representation of the Costas Condition for Costas Array Selection

IEEE Transactions on Aerospace and Electronic Systems, 2021
James Beard
exaly  

Hermite–Gaussian-Like Eigenvectors of the Discrete Fourier Transform Matrix Based on the Singular-Value Decomposition of Its Orthogonal Projection Matrices

IEEE Transactions on Circuits and Systems Part 1: Regular Papers, 2004
Magdy Tawfik Hanna, Waleed A Ahmed
exaly  

Singular and nonsingular eigenvectors for the Gaudin model

Journal of Mathematical Physics, 2001
Annamaria Kiss
exaly  

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