| ... | ... | @@ -15,4 +15,4 @@ To resolve this issue, we propose to use the Moore-Penrose pseudo-inverse method |
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`numpy.linalg.inv()` function.
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<img src="uploads/4692d03ff868fcc538ab06803102a7c3/pinv.png" width="440" ><img src="uploads/8d64ddc718f1fe06d54b62ca6028d123/pinv_off_diag.png" width="440" >
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In the above figures, the quantity 'pinv' refers to the `numpy.linalg.pinv` function. The figures indicate that the inner product using the right-hand inverse matrix is consistent with the left-hand inverse matrix, and also the off-diagonal elements are nearly equal to zero. Therefore, `pinv` more robust. However, the question is that why `pinv` is working better than the simple `inv` function. |
