model
Class ExponentialCorrelationFunction

java.lang.Object
  model.BasicCorrelationFunction
      model.DifferentiableCorrelationFunction
          model.SECorrelationFunction
              model.ExponentialCorrelationFunction

All Implemented Interfaces:

VariableInputDimension

public class ExponentialCorrelationFunction
extends SECorrelationFunction

Exponential correlation function.

corr(x1,x2) = exp(-sum_i |(x1_i - x2_i)/tau_i|).

Author:

dgorur

Nested Class Summary

Nested classes/interfaces inherited from class model.BasicCorrelationFunction

BasicCorrelationFunction.TYPE

Field Summary

Fields inherited from class model.DifferentiableCorrelationFunction

gradient

Fields inherited from class model.BasicCorrelationFunction

tauVec

Constructor Summary

ExponentialCorrelationFunction()

Method Summary

double	apply(cern.colt.matrix.DoubleMatrix1D x1, cern.colt.matrix.DoubleMatrix1D x2) Computes the correlation between the outputs at x1 and x2.
void	gradient(cern.colt.matrix.DoubleMatrix1D x1, cern.colt.matrix.DoubleMatrix1D x2, double[] g) The same as DifferentiableCorrelationFunction.gradient(DoubleMatrix1D, DoubleMatrix1D), but places the result in the supplied array.

Methods inherited from class model.SECorrelationFunction

apply

Methods inherited from class model.DifferentiableCorrelationFunction

getInstance, gradient, gradient, gradient, gradient, setInputDimension

Methods inherited from class model.BasicCorrelationFunction

apply, apply, apply, getInputDimension, getInstance, getTau, setTau

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

ExponentialCorrelationFunction

public ExponentialCorrelationFunction()

Method Detail

apply

public double apply(cern.colt.matrix.DoubleMatrix1D x1,
                    cern.colt.matrix.DoubleMatrix1D x2)

Description copied from class: BasicCorrelationFunction

Computes the correlation between the outputs at x1 and x2.

Overrides:

apply in class SECorrelationFunction

Parameters:

x1 - an input location.

x2 - another input location.

Returns:

the correlation between outputs at these two locations.

gradient

public void gradient(cern.colt.matrix.DoubleMatrix1D x1,
                     cern.colt.matrix.DoubleMatrix1D x2,
                     double[] g)

Description copied from class: DifferentiableCorrelationFunction

The same as DifferentiableCorrelationFunction.gradient(DoubleMatrix1D, DoubleMatrix1D), but places the result in the supplied array.

Overrides:

gradient in class SECorrelationFunction

Parameters:

x1 - the first point.

x2 - the second point.

g - array to hold the result.