How to compute the SVD of $2\times 2$ matrices? What's an efficient algorithm to get the SVD of $2\times 2$ matrices?
I've found papers about doing SVD on $2\times 2$ triangular matrices, and I've seen the analytic formula to get the singular values of a $2\times 2$ matrix. But how to use either of these to get the SVD of an arbitrary $2\times 2$ matrix?
Are the general algorithms built on these, or are these just some special cases?

The SVD of a $2\times 2$ matrix has a closed-form formula, which can be worked out by writing the rotation matrices in terms of a single unknown angle each, and then solving for those angles as well as the singular values.
It is worked out here, for instance.
