Table Of Contents
Generalized SVD Decomposition (G Dataflow)
Computes the generalized singular value decomposition (GSVD) of a matrix pair.
matrix A
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.
matrix B
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.
singular values only?
SVD option
Value specifying how the node performs the decomposition.
| Name | Value | Description |
|---|---|---|
| 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
error in
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
singular values
Generalized singular values of the input matrix pair (matrix A, matrix B).
matrix U
The U matrix of the GSVD results.
matrix V
The V matrix of the GSVD results.
matrix C
The C matrix of the GSVD results.
matrix S
The S matrix of the GSVD results.
error out
Error information.
The node produces this output 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.
matrix R
The R matrix of the GSVD results.
Algorithm for Calculating Generalized SVD Decomposition
The following expressions define the generalized singular value decomposition of a matrix pair (A, B).
A = UCR'
B = VSR'
where U and V are orthogonal matrices and R is a square matrix.
When k is the rank of matrix , 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