/*
* Encog(tm) Core v3.4 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2016 Heaton Research, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.neural.art;
import org.encog.ml.BasicML;
/**
* Adaptive Resonance Theory (ART) is a form of neural network developed
* by Stephen Grossberg and Gail Carpenter. There are several versions
* of the ART neural network, which are numbered ART-1, ART-2 and ART-3.
* The ART neural network is trained using either a supervised or
* unsupervised learning algorithm, depending on the version of ART being
* used. ART neural networks are used for pattern recognition and prediction.
*
* Plasticity is an important part for all Adaptive Resonance Theory (ART)
* neural networks. Unlike most neural networks, ART networks do not have
* a distinct training and usage stage. The ART network will learn as it is
* used.
*/
public class ART extends BasicML {
/**
* Serial id.
*/
private static final long serialVersionUID = 1L;
/**
* Neural network property, the A1 parameter.
*/
public static final String PROPERTY_A1 = "A1";
/**
* Neural network property, the B1 parameter.
*/
public static final String PROPERTY_B1 = "B1";
/**
* Neural network property, the C1 parameter.
*/
public static final String PROPERTY_C1 = "C1";
/**
* Neural network property, the D1 parameter.
*/
public static final String PROPERTY_D1 = "D1";
/**
* Neural network property, the L parameter.
*/
public static final String PROPERTY_L = "L";
/**
* Neural network property, the vigilance parameter.
*/
public static final String PROPERTY_VIGILANCE = "VIGILANCE";
/**
* Neural network property for no winner.
*/
public static final String PROPERTY_NO_WINNER = "noWinner";
/**
* {@inheritDoc}
*/
@Override
public void updateProperties() {
// unneeded
}
}