| class MLPLibrary { | |
| public: | |
| MLPLibrary(int inputSize, int hiddenSize, int outputSize, float learningRate); | |
| void initialize(); | |
| void trian(float input[MAX_INPUT_SIZE], float target[MAX_OUTPUT_SIZE]); | |
| void predict(float input[MAX_INPUT_SIZE], float output[MAX_OUTPUT_SIZE]); | |
| private: | |
| int numInputs; | |
| int numHidden; | |
| int numOutputs; | |
| float learningRate; | |
| float inputLayer[MAX_INPUT_SIZE]; | |
| float hiddenLayer[MAX_HIDDEN_SIZE]; | |
| float outputLayer[MAX_OUTPUT_SIZE]; | |
| float inputHiddenWeights[MAX_INPUT_SIZE][MAX_HIDDEN_SIZE]; | |
| float hiddenOutputWeights[MAX_HIDDEN_SIZE][MAX_OUTPUT_SIZE]; | |
| float hiddenLayerBiases[MAX_HIDDEN_SIZE]; | |
| float outputLayerBiases[MAX_OUTPUT_SIZE]; | |
| float hiddenLayerErrors[MAX_HIDDEN_SIZE]; | |
| float outputLayerErrors[MAX_OUTPUT_SIZE]; | |
| float sigmoid(float x); | |
| }; | |