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📄 kohonenneuronwithtired.java

📁 Kohonen network nural, framework for java developer
💻 JAVA
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/*** Copyright (c) 2006, Seweryn Habdank-Wojewodzki* Copyright (c) 2006, Janusz Rybarski** All rights reserved.* * Redistribution and use in source and binary forms,* with or without modification, are permitted provided* that the following conditions are met:** Redistributions of source code must retain the above* copyright notice, this list of conditions and the* following disclaimer.** Redistributions in binary form must reproduce the* above copyright notice, this list of conditions* and the following disclaimer in the documentation* and/or other materials provided with the distribution.** THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS* AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR* A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL* THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF* USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)* HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,* WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY* WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED* OF THE POSSIBILITY OF SUCH DAMAGE.*/package network;import activationFunction.ActivationFunctionModel;/** * Class representing <B> kohenen neuron with tiredness</B>  * with specyfied activation function * @author Janusz Rybarski * e-mail: janusz.rybarski AT ae DOT krakow DOT pl * @author Seweryn Habdank-Wojewdzki * e-mail: habdank AT megapolis DOT pl * @version 1.0 2006/07/13 */public class KohonenNeuronWithTired extends KohonenNeuron implements TiredNeuronModel{    /**     * Tiredness default set to 10     */    int tiredness = 10;        /**     * Creates new kohonen neuron with specyfied numbers of weight.      * Value of the weight is random where max value is definited by maxWeight.     * Activation function is definied by activationFunction parameter.     * @param weightNumber numbers of weight     * @param maxWeight max value of the weight     * @param activationFunction activation function     */    public KohonenNeuronWithTired(int weightNumber, double[] maxWeight, ActivationFunctionModel activationFunction) {        super(weightNumber,maxWeight,activationFunction);    }            /**     * Creates new kohonen neuron with weight specyfied by array and specified activation funciton.      * Numbers of weights are the same as length of the array.     * @param weightArray array of the weight     * @param activationFunction activation function     */    public KohonenNeuronWithTired(double[] weightArray,ActivationFunctionModel activationFunction) {        super(weightArray,activationFunction);    }            /**     * Set tiredness     * @param tiredness tiredness     */    public void setTiredness(int tiredness){        this.tiredness = tiredness;    }        /**     * Return value of tiredness     * @return value of tiredness     */    public int getTiredness(){        return this.tiredness;    }}

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