Artificial Intelligence208110 marksNumerical: ANN backpropagationLearning with Neural Networks
How can you relate synapse, dendrite, and axon in biological neural networks with the elements of artificial neural networks? Create a multi-layer ANN with input layer, hidden layer, and output layer. Assume necessary inputs and weights to the ANN and illustrate a single iteration of backpropagation
How can you relate synapse, dendrite, and axon in biological neural networks with the elements of artificial neural networks? Create a multi-layer ANN with input layer, hidden layer, and output layer. Assume necessary inputs and weights to the ANN and illustrate a single iteration of backpropagation algorithm to train the ANN.[10]
The question requires us to assume inputs and weights, so the worked example below uses these values: Inputs: $x1 = 0.5$, $x2 = 0.3$ Target: $t = 1.0$ Learning rate: $\alpha = 0.5$ Activation: Sigmoid $g(x) = \dfrac{1}{1+e^{-x}}$, derivative $g'(x) = g(x)(1-g(x))$ Biases: $0$ Initial weights: Wei...