Last Modified: January 12, 2018

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

A matrix with *m* rows and *p* columns.

This input accepts a 2D array of double-precision, floating point numbers or 2D array of complex double-precision, floating point numbers.

A matrix with *n* rows and *p* columns.

This input accepts a 2D array of double-precision, floating point numbers or 2D array of complex double-precision, floating point numbers.

Value specifying how the node performs the decomposition.

Name | Value | Description |
---|---|---|

Thin | 0 | Decomposes matrix Decomposes matrix |

Full | 1 | Decomposes matrix Decomposes matrix |

**Default: **Thin

Error conditions that occur before this node runs.

The node responds to this input according to standard error behavior.

Standard Error Behavior

Many nodes provide an **error in** input and an **error out** output so that the node can respond to and communicate errors that occur while code is running. The value of **error in** specifies whether an error occurred before the node runs. Most nodes respond to values of **error in** in a standard, predictable way.

**Default: **No error

Generalized singular values of the input matrix pair (**matrix A**, **matrix B**).

The *U* matrix of the GSVD results.

The *V* matrix of the GSVD results.

The *C* matrix of the GSVD results.

The *S* matrix of the GSVD results.

Error information.

The node produces this output according to standard error behavior.

Standard Error Behavior

**error in** input and an **error out** output so that the node can respond to and communicate errors that occur while code is running. The value of **error in** specifies whether an error occurred before the node runs. Most nodes respond to values of **error in** in a standard, predictable way.

The *R* matrix of the GSVD results.

The following expressions define the generalized singular value decomposition of a matrix pair (*A*, *B*).

*A* = *U**C**R*'

*B* = *V**S**R*'

where *U* and *V* are orthogonal matrices and *R* is a square matrix.

When *k* is the rank of matrix
$\left(\begin{array}{c}A\\ B\end{array}\right)$, then the first *k* diagonal elements of matrix *C*’*C* + *S*’*S* are ones and all of the other elements are zeros. The square roots of the first *k* diagonal elements of *C*’*C* and *S*’*S* determine the numerators and denominators of the generalized singular values, respectively.

**Where This Node Can Run: **

Desktop OS: Windows

FPGA: Not supported

Web Server: Not supported in VIs that run in a web application