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In the above figures, the quantity 'inv' refers to the `numpy.linalg.inv()` function. The quantity 'k' refers to the index of the off-diagonal array; k>0 for diagonals above the main diagonal, and k<0 for diagonals below the main diagonal.
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To resolve this issue, we propose to use the Moore-Penrose pseudo-inverse method. |
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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). |
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