我正在嘗試XOR用 Java構(gòu)建一個(gè)基本的神經(jīng)網(wǎng)絡(luò)來計(jì)算邏輯函數(shù)。該網(wǎng)絡(luò)有兩個(gè)輸入神經(jīng)元，一個(gè)包含三個(gè)神經(jīng)元的隱藏層和一個(gè)輸出神經(jīng)元。但是經(jīng)過幾次迭代后，輸出中的誤差變?yōu)镹aN。我已經(jīng)瀏覽了其他實(shí)現(xiàn)神經(jīng)網(wǎng)絡(luò)的實(shí)現(xiàn)和教程，但我找不到錯(cuò)誤。我覺得問題在于我的落后功能。請(qǐng)幫助我理解我哪里出錯(cuò)了。我的代碼：import org.ejml.simple.SimpleMatrix;import java.util.ArrayList;import java.util.List;import java.util.Random;// SimpleMatrix constructor format: SimpleMatrix(rows, cols)//The layers are represented as a matrix with 1 row and multiple columns (row vector)public class Network {    private SimpleMatrix inputs, outputs, hidden, W1, W2, predicted;    static final double LEARNING_RATE = 0.3;    Network(List<double[]> ips, List<double[]> ops){        hidden = new SimpleMatrix(1, 3);        W1 = new SimpleMatrix(ips.get(0).length, hidden.numCols());        W2 = new SimpleMatrix(hidden.numCols(), ops.get(0).length);        initWeights(W1,W2);        for(int i=0;i<5000;i++){            for(int j=0;j<ips.size();j++){                train(ips.get(j), ops.get(j));            }        }        System.out.println("Trained");    }    //Prints output matrix    SimpleMatrix predict(double[] ip){        SimpleMatrix bkpInputs = inputs.copy();        SimpleMatrix bkpOutputs = outputs.copy();        inputs = new SimpleMatrix(1, ip.length);        inputs.setRow(0, 0, ip);        forward();        inputs = bkpInputs;        outputs = bkpOutputs;        predicted.print();        return predicted;    }    void train(double[] inputs, double[] outputs){        this.inputs = new SimpleMatrix(1, inputs.length);        this.inputs.setRow(0, 0, inputs);        this.outputs = new SimpleMatrix(1, outputs.length);        this.outputs.setRow(0,0,outputs);        this.predicted = new SimpleMatrix(1,outputs.length);        forward();        backward();    }