C++ Neural Networks and Fuzzy Logic: Preface



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C neural networks and fuzzy logic

Listing 7.1 Header file for the backpropagation simulator

// layer.h            V.Rao, H. Rao

// header file for the layer class hierarchy and

// the network class

C++ Neural Networks and Fuzzy Logic:Preface

C++ Classes and Class Hierarchy

126



#define MAX_LAYERS    5

#define MAX_VECTORS   100

class network;

class layer

{

protected:



       int num_inputs;

       int num_outputs;

       float *outputs;// pointer to array of outputs

       float *inputs; // pointer to array of inputs, which

                      // are outputs of some other layer

       friend network;

public:

       virtual void calc_out()=0;

};

class input_layer: public layer



{

private:


public:

       input_layer(int, int);

       ~input_layer();

       virtual void calc_out();

};

class middle_layer;



class output_layer:   public layer

{

protected:



       float * weights;

       float * output_errors;    // array of errors at output

       float * back_errors;      // array of errors back−propagated

       float * expected_values;  // to inputs

   friend network;

public:


       output_layer(int, int);

       ~output_layer();

       virtual void calc_out();

       void calc_error(float &);

       void randomize_weights();

       void update_weights(const float);

       void list_weights();

       void write_weights(int, FILE *);

       void read_weights(int, FILE *);

       void list_errors();

       void list_outputs();

C++ Neural Networks and Fuzzy Logic:Preface

C++ Classes and Class Hierarchy

127



};

class middle_layer:   public output_layer

{

private:


public:

    middle_layer(int, int);

    ~middle_layer();

       void calc_error();

};

class network



{

private:


    layer *layer_ptr[MAX_LAYERS];

    int number_of_layers;

    int layer_size[MAX_LAYERS];

    float *buffer;

    fpos_t position;

    unsigned training;

public:

    network();

    ~network();

       void set_training(const unsigned &);

       unsigned get_training_value();

       void get_layer_info();

       void set_up_network();

       void randomize_weights();

       void update_weights(const float);

       void write_weights(FILE *);

       void read_weights(FILE *);

       void list_weights();

       void write_outputs(FILE *);

       void list_outputs();

       void list_errors();

       void forward_prop();

       void backward_prop(float &);

       int fill_IObuffer(FILE *);

       void set_up_pattern(int);

};

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C++ Neural Networks and Fuzzy Logic:Preface

C++ Classes and Class Hierarchy

128




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