3 ms·
Own favorite way to understand matrix multiplication: For any positive integer n, and any n x n matrix A of real and/or complex numbers, there are n x n matric
by graycat 3y ago
Own favorite way to understand matrix multiplication: For any positive integer n, and any n x n matrix A of real and/or complex numbers, there are n x n matrices U and H so that
A = UH
Each of U and H consists of real and/or complex numbers and all real numbers if A consists of all real numbers.
Here U is unitary which means that for any n x 1 vector (real and/or complex) x, Ux is the same as x except is rotated and/or reflected and the lengths
|x| = |Ux|
that is, U does not change lengths or distances and, thus, is a rigid motion (rotation, reflection).
For H, for x in a sphere S, the set of all Hx is just an
ellipsoid.
So, A = UH where U is a rigid motion, rotation, reflection, and H converts a sphere to an ellipsoid. The H is said to be Hermitian (there was a mathematician Hermite). Right, an ellipsoid has mutually perpendicular axes, and those are the eigenvectors of H.
My favorite result in linear algebra, and with a fairly short and simple proof.
- krackers 3y ago(For those looking for more info, this is called the polar decomposition. See https://csmbrannon.net/2013/02/14/illustration-of-polar-decomposition/ https://csmbrannon.net/2013/02/14/illustration-of-polar-deco...) I think the closely related SVD is more commonly used though, and Wikipedia has a nice animation https://en.wikipedia.org/wiki/Singular_value_decomposition https://en.wikipedia.org/wiki/Singular_value_decomposition