Moore-Penrose pseudoinverse
B = pinv(
returns the Moore-Penrose Pseudoinverse of matrix
A
)A
.
You can replace most uses of pinv
applied to a vector
b
, as in pinv(A)*b
, with
lsqminnorm(A,b)
to get the minimum-norm least-squares
solution of a system of linear equations. lsqminnorm
is
generally more efficient than pinv
, and it also supports
sparse matrices.
pinv
uses the singular value decomposition to form the
pseudoinverse of A
. Singular values along the diagonal of
S
that are smaller than tol
are treated as
zeros, and the representation of A
becomes:
The pseudoinverse of A
is then equal to:
decomposition
| inv
| lsqminnorm
| qr
| rank
| svd