Examples of NeighborhoodRBF

Examples of org.encog.neural.som.training.basic.neighborhood.NeighborhoodRBF

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  public SomColors() {
    this.setSize(640, 480);
    this.setDefaultCloseOperation(EXIT_ON_CLOSE);
    this.network = createNetwork();
    this.getContentPane().add(map = new MapPanel(this));
    this.gaussian = new NeighborhoodRBF(RBFEnum.Gaussian,MapPanel.WIDTH,
        MapPanel.HEIGHT);
    this.train = new BasicTrainSOM(this.network, 0.01, null, gaussian);
    train.setForceWinner(false);
    this.thread = new Thread(this);
    thread.start();
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Examples of org.encog.neural.som.training.basic.neighborhood.NeighborhoodRBF

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      nf = new NeighborhoodBubble(1);
    } else if (neighborhoodStr.equalsIgnoreCase("rbf")) {
      final String str = holder.getString(
          MLTrainFactory.PROPERTY_DIMENSIONS, true, null);
      final int[] size = NumberList.fromListInt(CSVFormat.EG_FORMAT, str);
      nf = new NeighborhoodRBF(size, t);
    } else if (neighborhoodStr.equalsIgnoreCase("rbf1d")) {
      nf = new NeighborhoodRBF1D(t);
    }
    if (neighborhoodStr.equalsIgnoreCase("single")) {
      nf = new NeighborhoodSingle();
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Examples of org.encog.neural.som.training.basic.neighborhood.NeighborhoodRBF

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      case 4:
        return new NeighborhoodBubble( (int)this.rbfWidth.getValue() );
      case 5:
        return new NeighborhoodSingle( );
      case 6:
        return new NeighborhoodRBF(RBFEnum.Gaussian, this.cols.getValue(), this.rows.getValue());
      case 7:
        return new NeighborhoodRBF(RBFEnum.MexicanHat, this.cols.getValue(), this.rows.getValue());
      case 8:
        return new NeighborhoodRBF(RBFEnum.Multiquadric, this.cols.getValue(), this.rows.getValue());
      case 9:
        return new NeighborhoodRBF(RBFEnum.InverseMultiquadric, this.cols.getValue(), this.rows.getValue());
      default:
        return null;
    }
  }
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Examples of org.encog.neural.som.training.basic.neighborhood.NeighborhoodRBF

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      nf = new NeighborhoodBubble(1);
    } else if (neighborhoodStr.equalsIgnoreCase("rbf")) {
      final String str = holder.getString(
          MLTrainFactory.PROPERTY_DIMENSIONS, true, null);
      final int[] size = NumberList.fromListInt(CSVFormat.EG_FORMAT, str);
      nf = new NeighborhoodRBF(size, t);
    } else if (neighborhoodStr.equalsIgnoreCase("rbf1d")) {
      nf = new NeighborhoodRBF1D(t);
    }
    if (neighborhoodStr.equalsIgnoreCase("single")) {
      nf = new NeighborhoodSingle();
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