Our objective is to classify the input pattern P described in question 3. A Set value...

 
 

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Our objective is to classify the input pattern P described in question 3. A Set value of bias vector equal to number of input elements 1) Initialise W' of the first layer with the appropriate values 2) Initialise b' the bias vector to number the input elements 3) Initialise W of the second layer to the appropriate values with E-0.6 4) Calculate for P the a. Output of First layer to po or pa by the use of a Neural newk b. The outputs of the second layer until convergence c. Classify P to the corresponding classes apple or orange Question 3: PLOKI/CLO 1/50 11 Xx1 1. The following ANN is called: 2. It is composed of two layers: the first layer is called: 3. The second layer is called: Wi SKR bi 5x1 (+) ni 5x1 al Sx1 Marking Schene 0.3 for each 13,3 a = purelin (W'p+b) W SX5 n(t+1) a(r+1) 4 5x1 S a(0) = a 5x1 D a() 3x1 a(+1)= poslin (Wa(t)) Our objective is to classify the input pattern P described in question 3. A Set value of bias vector equal to number of input elements 1) Initialise W' of the first layer with the appropriate values 2) Initialise b' the bias vector to number the input elements 3) Initialise W of the second layer to the appropriate values with E-0.6 4) Calculate for P the a. Output of First layer to po or pa by the use of a Neural newk b. The outputs of the second layer until convergence c. Classify P to the corresponding classes apple or orange Question 3: PLOKI/CLO 1/50 11 Xx1 1. The following ANN is called: 2. It is composed of two layers: the first layer is called: 3. The second layer is called: Wi SKR bi 5x1 (+) ni 5x1 al Sx1 Marking Schene 0.3 for each 13,3 a = purelin (W'p+b) W SX5 n(t+1) a(r+1) 4 5x1 S a(0) = a 5x1 D a() 3x1 a(+1)= poslin (Wa(t))

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Answer Step 1 Neural Network Setup Set the bias vector b equal to the number of input elements Initi... View the full answer