Package org.esa.snap.core.nn

Class NNffbpAlphaTabFast

java.lang.Object
org.esa.snap.core.nn.NNffbpAlphaTabFast
public class NNffbpAlphaTabFast extends Object
This class is for using a Neural Net (NN) of type ffbp in a Java program. The program for training such a NN "ffbp1.0" was written in C by

  • Constructor Details

    • NNffbpAlphaTabFast

      public NNffbpAlphaTabFast(String neuralNet) throws IOException
      Creates a neural net by reading the definition from the string.
      Parameters:
      neuralNet - the neural net definition as a string
      Throws:
      IOException - if the neural net could not be read

    • NNffbpAlphaTabFast

      public NNffbpAlphaTabFast(InputStream neuralNetStream) throws IOException
      Creates a neural net by reading the definition from the input stream.
      Parameters:
      neuralNetStream - the neural net definition as a input stream
      Throws:
      IOException - if the neural net could not be read

  • Method Details

    • getInmin

      public double[] getInmin()

    • setInmin

      public void setInmin(double[] inmin)

    • getInmax

      public double[] getInmax()

    • setInmax

      public void setInmax(double[] inmax)

    • getOutmin

      public double[] getOutmin()

    • getOutmax

      public double[] getOutmax()

    • calcJacobi

      public NNCalc calcJacobi(double[] nnInp)
      Method calcJacobi The NN is used. For a given input vector the corresponding output vector together with the corresponding Jacobi matrix is returned as an instance of class NNCalc.
      Parameters:
      nnInp - The vector contains the nn_ininput parameters (must be in right order).
      Returns:
      The output and corresponding Jacobi matrix of the NN.

    • calc

      public double[] calc(double[] nninp)
      Method calc The NN is used. For a given input vector the corresponding output vector is returned.
      Parameters:
      nninp - The vector contains the nn_ininput parameters (must be in right order).
      Returns:
      The nn_out-long output vector.