Last Modified: January 12, 2018

Determines multiple minima of an *n*-dimension function in a given interval using the conjugate gradient method.

Value that determines whether this node uses the derivatives in the algorithm.

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

Without Derivatives | 0 | Does not use the derivatives in the algorithm. |

With Derivatives | 1 | Uses the derivatives in the algorithm. |

**Default: **Without Derivatives

Algorithm this node uses to compute the derivatives.

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

Fletcher-Reeves | 0 | Uses the Fletcher-Reeves method. |

Polak-Ribiere | 1 | Uses the Polak-Ribiere method. |

**Default: **Fletcher-Reeves

Formula that defines the objective function. The formula can contain any number of valid variables

Names of the variables.

Variable names must start with a letter or an underscore followed by any number of alphanumeric characters or underscores.

Point in *n* dimension at which the optimization starts.

Point in *n* dimension at which the optimization ends.

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

Accuracy of the minimum of the objective function.

**Default: **1E-08

Number of the randomly chosen start points of the optimization. These points belong to the interval (**start**, **end**).

**Default: **5

Determined values of the variables where the objective function has the local minimum value. Each row contains *n* elements that represent the values of the *n* variables.

The values are an approximation of the variables where the objective function has the local minimum value.

Values of the objective function at each row of **minima**.

The values are an approximation of the actual minimum value of the objective function.

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.

**Where This Node Can Run: **

Desktop OS: Windows

FPGA: Not supported

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