public SinglePerceptronAND() {
// create training set (logical AND function)：創(chuàng)建訓(xùn)練集（符合邏輯與函數(shù)）
DataSet trainingSet = new DataSet(2, 1);trainingSet.addRow(...);
// create perceptron neural network：創(chuàng)建感知機(jī)(兩個(gè)入，一個(gè)出，就是最簡(jiǎn)單的單層一個(gè)神經(jīng)元的神經(jīng)網(wǎng)絡(luò))
NeuralNetwork myPerceptron = new Perceptron(2, 1);
// learn the training set：學(xué)習(xí)這個(gè)訓(xùn)練集，就是為了得到神經(jīng)網(wǎng)絡(luò)的參數(shù)
myPerceptron.learn(trainingSet);
// test perceptron：測(cè)試這個(gè)感知機(jī)，檢驗(yàn)它訓(xùn)練的參數(shù)是否正確
myPerceptron.setInput(trainingSet.get(0).getInput());
myPerceptron.calculate();
System.out.print("Input: " + Arrays.toString(trainingElement.getInput()));
System.out.println(" Output: " + Arrays.toString(networkOutput));
}