The Sherman-Morrison identity deals with the inversion of a rank-\(1\) perturbed matrix. In short, it states that its inverse is also a rank-\(1\) perturbed matrix. Most notably it can be used to significantly speed up the computations of the inverse of the total rank-1 perturbed matrix, if the inverse of the pertubed matrix is already known.
The special case of the Sherman-Morrison stated that the inversion of a rank-\(1\) perturbed identity matrix is also a rank-\(1\) perturbed identity matrix.
\[ (I + uv^\top )^{-1} = I - \frac{uv^\top }{1 + v^\top u}\ = I - u(1 + v^\top u)^{-1}v^\top \]Now since needs to be equal to \(I\) for all values of \(u\) and \(v\) we must have the expression inside the parenthesis must be 0 from which we can assert that
\[ \alpha = -(1 + v^\top u)^{-1}. \]Inserting this into our assumption the formula follows.
The first expression is how the formula is usually stated. However, I like the last form better since it naturally extends to the Sherman-Morrison-Woodbury formula. It also makes it easier to visualize what is doing on
We can generalize the formula to a perturbation of a general (invertible) matrix
\[ (A + uv^\top )^{-1} = A^{-1} - \frac{A^{-1}uv^\top A^{-1}}{1 + v^\top A^{-1}u} = A^{-1} - A^{-1}u\left(1 + v^\top A^{-1}u\right)^{-1}v^\top A^{-1}. \]Again the first expression is how the formula usually is stated, while the second is how I personally like to think of it. Again the formula can be visualized.