@@ -14,5 +14,5 @@ In the above figures, the quantity 'inv' refers to the `numpy.linalg.inv()` func
To resolve this issue, we propose to use the Moore-Penrose pseudo-inverse method. This method calculates the generalized inverse of a matrix using its singular-value decomposition (SVD) and including all large singular values. We use the numpy inbuild function [`numpy.linalg.pinv()`](https://numpy.org/doc/stable/reference/generated/numpy.linalg.pinv.html). At this moment, let us focus on the above comparison as we showed for the
