Parker Banks / mbeddedNets

Generates neural net instances through genetic algorithm for use in task learning by m3pi. Reward determined by detection of black areas on arena floor, or by amount of area explored in limited time. Due to memory size, limited # of nets.

Dependencies:   Ping m3pimaze mbed

Code/CNeuralNet.h

Committer:
parkbanks
Date:
2015-04-23
Revision:
0:ac93d9db8dbd

File content as of revision 0:ac93d9db8dbd:

#ifndef CNEURALNET_H
#define CNEURALNET_H

#include <vector>
#include <fstream>
#include <math.h>
#include "utils.h"

using namespace std;

// Neuron Struct
struct SNeuron
{
    int m_NumInputs; //the number of inputs into the neuron
    vector<float>  m_vecWeight; //the weights for each input
    SNeuron(int NumInputs); //ctor
};


// Neuron Layer Struct
struct SNeuronLayer
{
    int m_NumNeurons; //number of neurons in layer
    vector<SNeuron>     m_vecNeurons; //the layer of neurons
    SNeuronLayer(int NumNeurons, int NumInputsPerNeuron);
};


// Neural Net
class CNeuralNet
{   
private:   
    int m_NumInputs;
    int m_NumOutputs;
    int m_NumHiddenLayers;
    int m_NeuronsPerHiddenLyr;
    vector<SNeuronLayer> m_vecLayers;//storage for each neuron layer 

public:
    CNeuralNet();
    void CreateNet();
    vector<float> GetWeights()const; //weights from ANN
    int GetNumberOfWeights()const; //returns number of weights in net
    void PutWeights(vector<float> &weights); //replaces weights
    vector<float> Update(vector<float> &inputs); //gets outputs from net    
    inline float Sigmoid(float activation, float response); //sigmoid function
};

#endif