List questions from eigenvalues-eigenvectors

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In Finite Dimensional $\mathbb{C}[[x]]$ Modules, $x$ is Nilpotent

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Eigenvalues of the second exterior power of a linear operator

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How to find SVD and eigenvalue decomposition of these matrices?

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Two eigenvalues with one eigenvector, is the matrix diagonalizable?

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Geometric interpretation of why some matrices don't have eigenvalues

Published on 23 Sep 2018 - 11:35

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On the eigenvalue of a particular kind of matrix

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Eigenvalue of $(\partial_\tau-\frac{1}{2}\triangledown^2_x+1-\xi(\vec{x},\tau))\Psi(\vec{x},\tau)=\lambda\Psi(\vec{x},\tau)$

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Difficulty Understanding the Last Step of Principal Component Analysis (PCA)

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Does maximizing the Rayleigh quotient using the method of Lagrange multipliers require the matrix to be positive semidefinite?

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Calculate the Eigenvalue of a 3x3 matrix

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Mahalanobis Distance and Linear algebra

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Show that the matrix $A = \begin{bmatrix} 2 & 0 \\ -1 & 2 \end{bmatrix}$ is not diagonalizable.

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Can eigenvalues be outside of the scalar field of a vector space?

Published on 25 Mar 2026 - 1:17

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Prove that any real symmetrical matrix is guaranteed to have an eigendecomposition

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List Question

if $A+A^T$ is stable, then is $A$ also stable?

In Finite Dimensional $\mathbb{C}[[x]]$ Modules, $x$ is Nilpotent

Eigenvalues of the second exterior power of a linear operator

How to find SVD and eigenvalue decomposition of these matrices?

Two eigenvalues with one eigenvector, is the matrix diagonalizable?

Geometric interpretation of why some matrices don't have eigenvalues

On the eigenvalue of a particular kind of matrix

Eigenvalue of $(\partial_\tau-\frac{1}{2}\triangledown^2_x+1-\xi(\vec{x},\tau))\Psi(\vec{x},\tau)=\lambda\Psi(\vec{x},\tau)$

Difficulty Understanding the Last Step of Principal Component Analysis (PCA)

Does maximizing the Rayleigh quotient using the method of Lagrange multipliers require the matrix to be positive semidefinite?

Calculate the Eigenvalue of a 3x3 matrix

Mahalanobis Distance and Linear algebra

Show that the matrix $A = \begin{bmatrix} 2 & 0 \\ -1 & 2 \end{bmatrix}$ is not diagonalizable.

Can eigenvalues be outside of the scalar field of a vector space?

Prove that any real symmetrical matrix is guaranteed to have an eigendecomposition

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