Linear Algebra

Diagnolizing a matrix is a transformation using its eigen space.

$$ \mathbf{A} \ast \mathbf{B} = \left(\mathbf{A}_{ij} \otimes \mathbf{B}_{ij}\right)_{ij} $$

Given a matrix $\mathbf X \to X_{m}^{\phantom{m}n}$, we can decompose it into three matrices $$ …

Tucker decomposition of a generalization of SVD to higher ranks

To find the eigenvectors $\mathbf x$ of a matrix $\mathbf A$, we construct the eigen equation $$ …

Eigenstates of a very special matrix