Performs a discrete differentiation of the sampled signal X.


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Inputs/Outputs

  • c1ddbl.png X —

    X is the sampled signal from time 0 to n – 1 where n is the number of elements in X.

  • c1ddbl.png Initial Condition —

    Initial Condition specifies the initial condition of X in the differentiation calculation.

    If method is 2nd Order Central or Backward, the VI uses the first element in Initial Condition to calculate the derivative. If method is 4th Order Central, the VI uses the first two elements in Initial Condition to calculate the derivative. The default is [0].

  • c1ddbl.png Final Condition —

    Final Condition specifies the final condition of X in the differentiation calculation.

    If method is 2nd Order Central or Forward, the VI uses the first element in Final Condition to calculate the derivative. If method is 4th Order Central, the VI uses the first two elements in Final Condition to calculate the derivative. The default is [0].

  • cdbl.png dt —

    dt is the sampling interval and must be greater than zero. The default is 1.0.

    If dt is less than or equal to zero, the VI sets dX/dt to an empty array and returns an error.

  • cu16.png method —

    method specifies the differentiation method.

    02nd Order Central (default)
    14th Order Central
    2Forward
    3Backward
  • i1ddbl.png dX/dt —

    dX/dt is the derivative of the input signal X.

  • ii32.png error —

    error returns any error or warning from the VI. You can wire error to the Error Cluster From Error Code VI to convert the error code or warning into an error cluster.

    • The differentiation f(t) of a function F(t) is defined as

    Let Y represent the sampled output sequence dX/dt.

    If method is 2nd Order Central, Y is given by the following equation:

    for i = 0, 1, 2, …, n – 1,

    where n is the number of samples in x(t), x–1 is the first element in Initial Condition, and xn is the first element in Final Condition.

    If method is 4th Order Central, Y is given by the following equation:

    for i = 0, 1, 2, …, n – 1,

    where n is the number of samples in x(t), x–2 and x–1 are the first and second elements in Initial Condition, xn and xn + 1 are the first and second elements in Final Condition.

    If method is Forward, Y is given by the following equation:

    for i = 0, 1, 2, …, n – 1,

    where n is the number of samples in x(t) and xn is the first element in Final Condition.

    If method is Backward, Y is given by the following equation:

    for i = 0, 1, 2, …, n – 1,

    where n is the number of samples in x(t) and x–1 is the first element in Initial Condition.

    The Initial Condition and Final Condition minimize the error at the boundaries.

    Examples

    Refer to the following example files included with LabVIEW.

    • labview\examples\Mathematics\Probability and Statistics\Probability Density.vi