org.encog.neural.activation
Class ActivationBiPolar
java.lang.Object
org.encog.neural.activation.BasicActivationFunction
org.encog.neural.activation.ActivationBiPolar
- All Implemented Interfaces:
- java.io.Serializable, java.lang.Cloneable, ActivationFunction, EncogPersistedObject
public class ActivationBiPolar
- extends BasicActivationFunction
BiPolar activation function. This will scale the neural data into the bipolar
range. Greater than zero becomes 1, less than or equal to zero becomes -1.
- Author:
- jheaton
- See Also:
- Serialized Form
| Methods inherited from class java.lang.Object |
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
ActivationBiPolar
public ActivationBiPolar()
activationFunction
public void activationFunction(double[] d)
- Implements the activation function. The array is modified according
to the activation function being used. See the class description
for more specific information on this type of activation function.
- Parameters:
d - The input array to the activation function.
clone
public java.lang.Object clone()
- Specified by:
clone in interface EncogPersistedObject- Overrides:
clone in class BasicActivationFunction
- Returns:
- The object cloned.
createPersistor
public Persistor createPersistor()
- Create a Persistor for this activation function.
- Specified by:
createPersistor in interface EncogPersistedObject- Overrides:
createPersistor in class BasicActivationFunction
- Returns:
- The persistor.
derivativeFunction
public void derivativeFunction(double[] d)
- Implements the activation function derivative. The array is modified
according derivative of the activation function being used. See the
class description for more specific information on this type of
activation function. Propagation training requires the derivative.
Some activation functions do not support a derivative and will throw
an error.
- Parameters:
d - The input array to the activation function.
hasDerivative
public boolean hasDerivative()
- Returns:
- Return false, bipolar has no derivative.