コード例 #1
0
        public UnifiedCameraNeuralNetwork(int inputLayerSize, int hiddenLayerSize, int outputLayerSize,
                                          float learningRate,
                                          bool isStochastic = true, float momentum = 0)
        {
            // Network functional parameters
            _nonLinearityFunc      = sigmoid;
            _nonLinearityFuncDeriv = sigmoidDerivative;
            _errorFunction         = meanSquareError;
            _errorFunctionDerv     = meanSquareErrorDerivative;

            // Network initialization
            this.LearningRate = learningRate;
            _momentum         = momentum;
            _inputLayerSize   = inputLayerSize;
            _hiddenLayerSize  = hiddenLayerSize;
            _outputLayerSize  = outputLayerSize;
            _input            = new Matrix(inputLayerSize + 1, 1); // Vector (+ 1 for bias)
            _expected         = new Matrix(outputLayerSize, 1);    // Vector

            // Add 1 for bias
            _hiddenLayerWeights          = new Matrix(_hiddenLayerSize, _inputLayerSize + 1);
            _outputLayerWeights          = new Matrix(_outputLayerSize, _hiddenLayerSize + 1);
            _prevHiddenLayerWeightsDelta = new Matrix(_hiddenLayerSize, _inputLayerSize + 1);
            _prevOutputLayerWeightsDelta = new Matrix(_outputLayerSize, _hiddenLayerSize + 1);

            _isStochastic        = isStochastic;
            _hiddenWeightUpdates = new Matrix(_hiddenLayerSize, _inputLayerSize + 1);
            _outputWeightUpdates = new Matrix(_outputLayerSize, _hiddenLayerSize + 1);
            _weightUpdatesCount  = 0;

            _random = new Random(RANDOM_SEED);
            randomizeWeights();
        }
コード例 #2
0
ファイル: AnnTester.cs プロジェクト: orperel/KinectAnywhere
        public static void runMatrixTest()
        {
            Matrix mat1 = new Matrix(3, 3);

            mat1[0, 0] = 1;
            mat1[0, 1] = 0;
            mat1[0, 2] = 0;
            mat1[1, 0] = 0;
            mat1[1, 1] = 1;
            mat1[1, 2] = 0;
            mat1[2, 0] = 0;
            mat1[2, 1] = 0;
            mat1[2, 2] = 1;

            Matrix mat2 = new Matrix(3, 3);

            mat2[0, 0] = 1;
            mat2[0, 1] = 0;
            mat2[0, 2] = 0;
            mat2[1, 0] = 0;
            mat2[1, 1] = 1;
            mat2[1, 2] = 0;
            mat2[2, 0] = 0;
            mat2[2, 1] = 0;
            mat2[2, 2] = 1;

            if (!mat1.Equals(mat2))
            {
                Console.WriteLine("Equal test #1 failed");
                return;
            }

            mat2[0, 0] = 0;

            if (mat1.Equals(mat2))
            {
                Console.WriteLine("Equal test #2 failed");
                return;
            }

            if (!mat1.Equals(Matrix.identity(3, 3)) || mat2.Equals(Matrix.identity(3, 3)))
            {
                Console.WriteLine("Equal test #3 failed");
                return;
            }

            float[] vals = new float[9];
            for (int i = 0; i < 9; i++)
            {
                vals[i] = i;
            }

            Matrix matVals  = new Matrix(vals);
            Matrix matClone = new Matrix(matVals);

            if (!matVals.Equals(matClone))
            {
                Console.WriteLine("Copy constructor failed");
                return;
            }

            Matrix mul = new Matrix(1, 9);

            mul = mul.transpose();
            mul.init(vals);
            if (!mul.Equals(matClone))
            {
                Console.WriteLine("Init failed");
                return;
            }

            matVals = new Matrix(3, 3);
            for (int i = 0; i < 3; i++)
            {
                for (int j = 0; j < 3; j++)
                {
                    matVals[i, j] = i * 3 + j;
                }
            }

            matClone = new Matrix(matVals);
            mul      = matVals.mul(mat1);

            if (!mul.Equals(matClone))
            {
                Console.WriteLine("Mul with identity failed");
                return;
            }

            mul = matVals.mul(matClone);

            if (mul.Equals(matClone))
            {
                Console.WriteLine("Mul with non-identity failed");
                return;
            }

            // Debug window zone
            Matrix add       = matClone + matVals;
            Matrix sub       = matClone - matVals;
            Matrix transpose = matClone.transpose();
            Matrix mulScalar = matClone * 0.5f;
            Matrix dot       = matClone.dot(matVals);

            Matrix.MatrixPerElementOperation testfunc1 = testMatrixPerElementOperation;
            Matrix.MatrixPerElementProduct   testfunc2 = testMatrixProduct;
            Matrix invoke1 = matClone.invoke(testfunc1);
            Matrix invoke2 = matClone.invoke(testfunc2, matVals);

            Console.WriteLine("Test ended");
        }