Scilab-Branch-5.3-GIT
- Scilab help
- Linear Algebra
- aff2ab
- balanc
- bdiag
- chfact
- chol
- chsolve
- classmarkov
- cmb_lin
- coff
- colcomp
- companion
- cond
- det
- eigenmarkov
- ereduc
- expm
- fstair
- fullrf
- fullrfk
- genmarkov
- givens
- glever
- gschur
- gspec
- hess
- householder
- im_inv
- inv
- kernel
- kroneck
- linsolve
- lsq
- lu
- lyap
- nlev
- orth
- pbig
- pencan
- penlaur
- pinv
- polar
- proj
- projspec
- psmall
- qr
- quaskro
- randpencil
- range
- rank
- rankqr
- rcond
- rowcomp
- rowshuff
- rref
- schur
- spaninter
- spanplus
- spantwo
- spec
- sqroot
- squeeze
- sva
- svd
- sylv
- trace
Please note that the recommended version of Scilab is 2025.0.0. This page might be outdated.
See the recommended documentation of this function
sva
singular value approximation
Calling Sequence
[U,s,V]=sva(A,k) [U,s,V]=sva(A,tol)
Arguments
- A
real or complex matrix
- k
integer
- tol
nonnegative real number
Description
Singular value approximation.
[U,S,V]=sva(A,k)
with k
an integer
>=1, returns U,S
and V
such that
B=U*S*V'
is the best L2 approximation of
A
with rank(B
)=k
.
[U,S,V]=sva(A,tol)
with tol
a real
number, returns U,S
and V
such that
B=U*S*V'
such that L2-norm of A-B
is at most tol
.
See Also
- svd — singular value decomposition
<< squeeze | Linear Algebra | svd >> |