Home > Support > NI Product Manuals > LabVIEW Communications System Design Suite 1.0 Manual

Computes the generalized singular value decomposition (GSVD) of a matrix pair.

connector_pane_image
datatype_icon

a

A matrix with m rows and p columns.

datatype_icon

b

A matrix with n rows and p columns.

datatype_icon

singular values only?

A Boolean specifying whether the node computes only the generalized singular values.

TRUE The node computes only singular values.
FALSE The node computes all the matrices in the generalized SVD decomposition.

Default: FALSE

datatype_icon

svd option

A value specifying how the node performs the decomposition.

Thin 0

Decomposes matrix A as the multiplication of matrix U (m x min(m,p)), C (min(m,p) x p) and transpose of R (p x p).

Decomposes matrix B as the multiplication of matrix V (n x min(n,p)), S (min(n,p) x p) and transpose of R (p x p).

Full 1

Decomposes matrix A as the multiplication of matrix U (m x m), C (m x p) and transpose of R (p x p).

Decomposes matrix B as the multiplication of matrix V (n x n), S (n x p) and transpose of R (p x p).

Default: Thin

datatype_icon

matrix r

R matrix of the GSVD results.

datatype_icon

singular values

Generalized singular values of matrix pair (a,b).

datatype_icon

matrix u

The U matrix of the GSVD results.

datatype_icon

matrix v

The V matrix of the GSVD results.

datatype_icon

matrix c

The C matrix of the GSVD results.

datatype_icon

matrix s

The S matrix of the GSVD results.

datatype_icon

error

A value that represents any error or warning that occurs when this node executes.