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A multilayer perceptron neural network model contains three input nodes (namely C1, C2, and C3), one hidden layer with two hidden nodes [namely H1 and H2), and an output layer with node T1. The table below shows the weight values and biases of the neural network model. From Into Weight BIAS H 1 -0.14 BIAS H2 0.36 C1 H 1 0.82 C1 H2 -2.33 C2 H 1 0.34 C2 H2 -0.90 C3 H 1 -0.25 C3 H2 0.80 BIAS T1 0.74 H 1 T1 0.58 H2 T1 -1.43 Consider an observation with inputs C1 = 0.1, C2 = 0.02, and C3 = 0.12. You must keep at least 4 decimal places in your calculations and in your answer for each subquestion. (a) Using a linear combination function, calculate the input value to the hidden nodes H1 and H2, respectively. [3 marks] (b) Using a hyperbolic tangent activation function, calculate the output value of each hidden node H1 and H2. resnectivelv