import java.util.Random; 
 
class Example{
    double input[];
    double output;
 
    Example(double[] in, double out){
        this.input = in;
        this.output = out;
    } 
}
 
class HiddenSigmoidUnit{
    double output, error;
    double input[];
    double w[];  
    double n = 0.05;  
    double bias = 1;
 
    static Random rand = new Random();
    HiddenSigmoidUnit(){ 
        w = new double[2];   
        int s = rand.nextBoolean()?1:-1;
        for(int i=0;i<w.length;++i)w[i] = s*rand.nextDouble();  
    } 
 
    public double computeOutput(double[] input){
        this.input = input;
        output = bias+w[0]*input[0] + w[1]*input[1];
        output = 1/(1+Math.pow(Math.E, -output));    
        return output;
    }
 
    public double computeError(double w, double outputUnitError){
        error = (output)*(1-output)*(outputUnitError*w);  
        return error;        
    }
 
    public void fixError(){  
        for(int i=0;i<input.length;++i) w[i] += n*error*input[i]; 
    }
}
 
class OutputUnit{
    double t, output, error;
    double input[];
    double w[];  
    double bias=1;
    double n = 0.05; 
 
    static Random rand = new Random();
 
    OutputUnit(int hUnits){ 
        w = new double[hUnits];
        int s = rand.nextBoolean()?1:-1;
        //Weights between -1 to 1
        for(int i=0;i<w.length;++i)w[i] = s*rand.nextDouble();
    } 
 
    public void computeOutput(double[] input) { 
        this.input = input;  
        output = bias+input[0]*w[0]+input[1]*w[1];
        output = 1/(1+Math.pow(Math.E, -output));   
    } 
 
    public void computeError(double t){ 
        this.t = t; 
        error = (output)*(1-output)*(t-output); 
    }
 
    public void fixError() {     
        for(int i=0;i<w.length;++i) w[i] += n*error*input[i]; 
    }   
} 
 
class Net{
    static Random rand = new Random();
    static OutputUnit outputUnit;
    static HiddenSigmoidUnit[] hlayer;
 
    static Example[] examples = {
            new Example(new double[]{0, 0}, 0),
            new Example(new double[]{0,  1}, 1),
            new Example(new double[]{1, 0}, 1),
            new Example(new double[]{1,  1}, 0)
    }; 
 
    public static void main(String[] args){  
        //units in hidden layer
        int nhidden = 2;
 
        //Holds hidden layers' units
        hlayer = new HiddenSigmoidUnit[nhidden];
 
        //Initialize
        for(int i=0;i<hlayer.length;++i)hlayer[i] = new HiddenSigmoidUnit();
        outputUnit = new OutputUnit(hlayer.length);
 
        //test multiple times for convergence to optimal values
        for(int check=0;check<100;++check){
 
            for(int i=0;i<hlayer.length;++i)hlayer[i] = new HiddenSigmoidUnit();
            outputUnit = new OutputUnit(hlayer.length);
 
            //iteration count
            for(int iteration = 0;;++iteration){ 
 
                //if count == 4, all the examples were classified correctly, break
                int count=0;
 
                //Shuffle examples
                /*
                for(int i=0;i<examples.length;++i){
                    for(int j=i+1;j<examples.length;++j){
                        int choose = rand.nextInt(j);
                        Example t = examples[choose];
                        examples[choose] = examples[j];
                        examples[j] = t;
                    }
                }
                */
 
                //for each example
                for(int i=0;i<examples.length;++i){
 
                    Example example = examples[i]; 
 
                    //collect the outputs from hidden layer to pass on to output unit
                    double[] outputsHLayer = new double[hlayer.length]; 
                    for(int j=0;j<hlayer.length;++j) outputsHLayer[j] = hlayer[j].computeOutput(example.input); 
 
                    //pass to output unit
                    outputUnit.computeOutput(outputsHLayer);
 
                    //Compute Errors for output and hidden layer units
                    //Passing the true output, compute outputUnit error
                    outputUnit.computeError(example.output);   
 
                    //compute hidden layer - units' error
                    for(int j=0;j<hlayer.length;++j) hlayer[j].computeError(outputUnit.w[j], outputUnit.error); 
 
                    //fix errors
                    outputUnit.fixError();
                    for(int j=0;j<hlayer.length;++j) hlayer[j].fixError();  
 
                    //check if output units result matches the current example
                    int o = outputUnit.output>0.5?1:0;
                    if(o==example.output)count++;
                } //end-for each example
 
                if(iteration>90000){
                    //Probably not going to converge to optimal values
                    System.out.println("\nIterations > 90000, stop...");
                    displayOutputs(); 
                    break;
                }
 
                //if it matches all examples, stop training
                if(count==examples.length){
                    System.out.println("\nTraining complete. No of iterations = "+iteration);
                    displayOutputs();
                    break;
                }
            } //end for-each 
        }//end for-each re-initialization
    }//end main
 
    //Apply the learned weights to all the examples
    public static void displayOutputs(){
        System.out.println("Displaying outputs for all examples... ");
        double[] outputsHLayer = new double[hlayer.length]; 
 
        for(int e=0;e<examples.length;++e){
            for(int j=0;j<hlayer.length;++j) {
                outputsHLayer[j] = hlayer[j].computeOutput(examples[e].input);
            } 
            outputUnit.computeOutput(outputsHLayer); 
            System.out.println(outputUnit.output);
        }
    }
}

import java.util.Random; 
 
class Example{
    double input[];
    double output;
    
    Example(double[] in, double out){
        this.input = in;
        this.output = out;
    } 
}

class HiddenSigmoidUnit{
    double output, error;
    double input[];
    double w[];  
    double n = 0.05;  
    double bias = 1;
    
    static Random rand = new Random();
    HiddenSigmoidUnit(){ 
        w = new double[2];   
        int s = rand.nextBoolean()?1:-1;
        for(int i=0;i<w.length;++i)w[i] = s*rand.nextDouble();  
    } 
    
    public double computeOutput(double[] input){
        this.input = input;
        output = bias+w[0]*input[0] + w[1]*input[1];
        output = 1/(1+Math.pow(Math.E, -output));    
        return output;
    }
       
    public double computeError(double w, double outputUnitError){
        error = (output)*(1-output)*(outputUnitError*w);  
        return error;        
    }
    
    public void fixError(){  
        for(int i=0;i<input.length;++i) w[i] += n*error*input[i]; 
    }
}
 
class OutputUnit{
    double t, output, error;
    double input[];
    double w[];  
    double bias=1;
    double n = 0.05; 

    static Random rand = new Random();
    
    OutputUnit(int hUnits){ 
        w = new double[hUnits];
        int s = rand.nextBoolean()?1:-1;
        //Weights between -1 to 1
        for(int i=0;i<w.length;++i)w[i] = s*rand.nextDouble();
    } 
    
    public void computeOutput(double[] input) { 
        this.input = input;  
        output = bias+input[0]*w[0]+input[1]*w[1];
        output = 1/(1+Math.pow(Math.E, -output));   
    } 
    
    public void computeError(double t){ 
        this.t = t; 
        error = (output)*(1-output)*(t-output); 
    }
    
    public void fixError() {     
        for(int i=0;i<w.length;++i) w[i] += n*error*input[i]; 
    }   
} 
 
class Net{
    static Random rand = new Random();
    static OutputUnit outputUnit;
    static HiddenSigmoidUnit[] hlayer;
    
    static Example[] examples = {
            new Example(new double[]{0, 0}, 0),
            new Example(new double[]{0,  1}, 1),
            new Example(new double[]{1, 0}, 1),
            new Example(new double[]{1,  1}, 0)
    }; 
    
    public static void main(String[] args){  
        //units in hidden layer
        int nhidden = 2;
        
        //Holds hidden layers' units
        hlayer = new HiddenSigmoidUnit[nhidden];
        
        //Initialize
        for(int i=0;i<hlayer.length;++i)hlayer[i] = new HiddenSigmoidUnit();
        outputUnit = new OutputUnit(hlayer.length);
         
        //test multiple times for convergence to optimal values
        for(int check=0;check<100;++check){
            
            for(int i=0;i<hlayer.length;++i)hlayer[i] = new HiddenSigmoidUnit();
            outputUnit = new OutputUnit(hlayer.length);
            
            //iteration count
            for(int iteration = 0;;++iteration){ 
                
                //if count == 4, all the examples were classified correctly, break
                int count=0;
                
                //Shuffle examples
                /*
                for(int i=0;i<examples.length;++i){
                    for(int j=i+1;j<examples.length;++j){
                        int choose = rand.nextInt(j);
                        Example t = examples[choose];
                        examples[choose] = examples[j];
                        examples[j] = t;
                    }
                }
                */
                
                //for each example
                for(int i=0;i<examples.length;++i){

                    Example example = examples[i]; 
                    
                    //collect the outputs from hidden layer to pass on to output unit
                    double[] outputsHLayer = new double[hlayer.length]; 
                    for(int j=0;j<hlayer.length;++j) outputsHLayer[j] = hlayer[j].computeOutput(example.input); 

                    //pass to output unit
                    outputUnit.computeOutput(outputsHLayer);
                    
                    //Compute Errors for output and hidden layer units
                    //Passing the true output, compute outputUnit error
                    outputUnit.computeError(example.output);   
                    
                    //compute hidden layer - units' error
                    for(int j=0;j<hlayer.length;++j) hlayer[j].computeError(outputUnit.w[j], outputUnit.error); 

                    //fix errors
                    outputUnit.fixError();
                    for(int j=0;j<hlayer.length;++j) hlayer[j].fixError();  
                    
                    //check if output units result matches the current example
                    int o = outputUnit.output>0.5?1:0;
                    if(o==example.output)count++;
                } //end-for each example
                
                if(iteration>90000){
                    //Probably not going to converge to optimal values
                    System.out.println("\nIterations > 90000, stop...");
                    displayOutputs(); 
                    break;
                }
                
                //if it matches all examples, stop training
                if(count==examples.length){
                    System.out.println("\nTraining complete. No of iterations = "+iteration);
                    displayOutputs();
                    break;
                }
            } //end for-each 
        }//end for-each re-initialization
    }//end main
    
    //Apply the learned weights to all the examples
    public static void displayOutputs(){
        System.out.println("Displaying outputs for all examples... ");
        double[] outputsHLayer = new double[hlayer.length]; 
                    
        for(int e=0;e<examples.length;++e){
            for(int j=0;j<hlayer.length;++j) {
                outputsHLayer[j] = hlayer[j].computeOutput(examples[e].input);
            } 
            outputUnit.computeOutput(outputsHLayer); 
            System.out.println(outputUnit.output);
        }
    }
}