public void testSensitivityMatrixCalculationFromSucceedingLayer() { Matrix weightMatrix1 = new Matrix(2, 1); weightMatrix1.Set(0, 0, -0.27); weightMatrix1.Set(1, 0, -0.41); Vector biasVector1 = new Vector(2); biasVector1.SetValue(0, -0.48); biasVector1.SetValue(1, -0.13); Layer layer1 = new Layer(weightMatrix1, biasVector1, new LogSigActivationFunction()); LayerSensitivity layer1Sensitivity = new LayerSensitivity(layer1); Vector inputVector1 = new Vector(1); inputVector1.SetValue(0, 1); layer1.FeedForward(inputVector1); Matrix weightMatrix2 = new Matrix(1, 2); weightMatrix2.Set(0, 0, 0.09); weightMatrix2.Set(0, 1, -0.17); Vector biasVector2 = new Vector(1); biasVector2.SetValue(0, 0.48); Layer layer2 = new Layer(weightMatrix2, biasVector2, new PureLinearActivationFunction()); Vector inputVector2 = layer1.GetLastActivationValues(); layer2.FeedForward(inputVector2); Vector errorVector = new Vector(1); errorVector.SetValue(0, 1.261); LayerSensitivity layer2Sensitivity = new LayerSensitivity(layer2); layer2Sensitivity.SensitivityMatrixFromErrorMatrix(errorVector); layer1Sensitivity .SensitivityMatrixFromSucceedingLayer(layer2Sensitivity); Matrix sensitivityMatrix = layer1Sensitivity.GetSensitivityMatrix(); Assert.AreEqual(2, sensitivityMatrix.GetRowDimension()); Assert.AreEqual(1, sensitivityMatrix.GetColumnDimension()); Assert.AreEqual(-0.0495, sensitivityMatrix.Get(0, 0), 0.001); Assert.AreEqual(0.0997, sensitivityMatrix.Get(1, 0), 0.001); }