The minverse X-Function generates an inverse matrix by dividing the adjoint by its determinant. When matrices do not have inverses or determinants, a Moore-Penrose pseudoinverse is computed.
For user-interface access to this function:
| Recalculate |
Controls recalculation of analysis results
For more information, see: Recalculating Analysis Results |
|---|---|
| Input Matrix |
Choose input matrix. For help with range controls, see: Specifying Your Input Data |
| Output Matrix |
Choose where to output the inverse matrix. For help with the range controls, see: Output Results |
For a square matrix of full rank
, the inverse matrix
(aka the reciprocal matrix), will satisfy the relationship:
where
is the identity matrix.
The calculation of
can be expressed as:
where
is the determinant of matrix
and
is the adjoint.
where
is the
matrix by elimination of the
column and
row of
.
When matrices do not have inverses or determinants, a Moore-Penrose pseudoinverse will be computed. It exists for any
matrix.
Given an
matrix
,
is the unique
pseudoinverse matrix. If
and A has full rank, then the
satisfies the following:
The computation is based on singular value decomposition (SVD) of the matrix
and any singular values within tolerance, are treated as zero. If the rank of
is not full, then the matrix will shrink to a smaller matrix.