# Find All Minima nD (Conjugate Gradient) (G Dataflow)

Determines the minima of an n-dimension function in a given n-dimension interval with the conjugate gradient method.  ## line minimization

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

Function under investigation. The formula can contain any number of valid variables.

Entering Valid Variables

This node accepts variables that use the following format rule: variables must start with a letter or an underscore followed by any number of alphanumeric characters or underscores. ## start

Point in n dimension at which the optimization process starts. ## end

Point in n dimension at which the optimization process ends. ## 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.

error in does not contain an error error in contains an error  If no error occurred before the node runs, the node begins execution normally.

If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.

If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.

Default: No error ## accuracy

Accuracy of the minimum of the formula.

The node stops running if the difference between two consecutive approximations equals to or is less than the value of accuracy.

Default: 1E-08 ## number of trials

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

Default: 5 ## minima

Matrix describing all local minima. ## f(minima)

Function values at the points minima. ## 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.

error in does not contain an error error in contains an error  If no error occurred before the node runs, the node begins execution normally.

If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.

If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.

Where This Node Can Run:

Desktop OS: Windows

FPGA: This product does not support FPGA devices