Table Of Contents

Find a Minimum nD (Quasi-Newton » Formula) (G Dataflow)

Version:
    Last Modified: January 12, 2018

    Uses the quasi-Newton method to determine a local minimum of a function of n independent variables defined with formulas.

    The quasi-Newton method converges fast for functions that are smooth and have first and second derivatives defined.

    connector_pane_image
    datatype_icon

    variables

    Names of the variables.

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

    datatype_icon

    objective function

    Formula that defines the objective function. 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.

    datatype_icon

    start

    Values of the variables at which the optimization starts.

    datatype_icon

    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

    datatype_icon

    stopping criteria

    Conditions that terminate the optimization.

    This node terminates the optimization if this node reaches all the tolerance thresholds or passes any of the maximum thresholds.

    datatype_icon

    function tolerance

    Minimum relative change in function values between two internal iterations.

    Definition of Relative Change in Function Values

    The relative change in function values between two internal iterations is defined as follows:

    abs ( f n f n 1 ) abs ( f n ) + ε

    where

    • fn is the function value of the current iteration
    • fn - 1 is the function value of the previous iteration
    • ε is the machine epsilon

    Default: 1E-06

    datatype_icon

    parameter tolerance

    Minimum relative change in parameter values between two internal iterations.

    Definition of Relative Change in Parameter Values

    The relative change in parameter values between two internal iterations is defined as follows:

    abs ( P n P n 1 ) abs ( P n ) + ε

    where

    • Pn is the parameter value of the current iteration
    • Pn - 1 is the parameter value of the previous iteration
    • ε is the machine epsilon

    Default: 1E-06

    datatype_icon

    gradient tolerance

    Minimum 2-norm of the gradient.

    Default: 1E-06

    datatype_icon

    maximum iterations

    Maximum number of iterations that the node runs in the optimization.

    Default: 100

    datatype_icon

    maximum function calls

    Maximum number of calls to the objective function allowed in the optimization.

    Default: 1000

    datatype_icon

    maximum time

    Maximum amount of time in seconds allowed for the optimization.

    Default: -1 — The optimization never times out.

    datatype_icon

    minimum

    Values of the variables where the objective function has the local minimum.

    datatype_icon

    f(minimum)

    Value of the objective function at minimum.

    datatype_icon

    function calls

    Number of times that this node called the objective function(s) in the optimization.

    datatype_icon

    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: Not supported

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


    Recently Viewed Topics