Version:

Last Modified: January 12, 2018

Finds the inverse of an input matrix, if the inverse exists.

Specifying the matrix type allows this node to execute more quickly by avoiding unnecessary computations, which could introduce numerical inaccuracy.

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

General | The input matrix is a matrix that you cannot describe with one of the other categories. |

Positive definite | The input matrix is positive-definite. |

Lower triangular | The input matrix is lower triangular. |

Upper triangular | The input matrix is upper triangular. |

**Default: **General

A square matrix.

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

If the matrix is singular or is not square, this node returns an empty array and an error.

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

The inverse matrix of the input matrix.

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.

If the input **matrix** is nonsingular, this node calculates the output **inverse matrix** by solving the linear system given by the following equation.

*A**B* = *I*

where

*A*is the input**matrix***B*is the output**inverse matrix***I*is the identity matrix

If *A* is a nonsingular matrix, you can show that the solution to the preceding system is unique and that it corresponds to the output **inverse matrix** of *A*, given by the following equation.

*B* = *A*^{-1}

Therefore, *B* is an inverse matrix.

The numerical implementation of the matrix inversion is not only numerically intensive, but because of its recursive nature, is also highly sensitive to round-off errors introduced by the floating-point numeric coprocessor. Although the computations use the maximum possible accuracy, this node cannot always solve for the system.

**Where This Node Can Run: **

Desktop OS: Windows

FPGA: Not supported

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