Input (copied from eigenvalues and eigenvectors Wikipedia entry): In linear algebra, an eigenvector (/ˈaɪɡən-/ EYE-gən-) or characteristic vector is a vector that has its direction unchanged by a given linear transformation. More precisely, an eigenvector, v, of a linear transformation, T, is scaled by a constant factor, λ, when the linear transformation is applied to it: T v = λ v. It is often important to know these vectors in linear algebra. The corresponding eigenvalue, characteristic value, or characteristic root is the multiplying factor λ.
Output: Eigenvectors are vectors that don't give a damn when a linear transformation tries to mess with them. They just scale up or down like they're at the gym. Mathematicians love these stubborn bastards for some reason.
Output: Eigenvectors are vectors that don't give a damn when a linear transformation tries to mess with them. They just scale up or down like they're at the gym. Mathematicians love these stubborn bastards for some reason.