Pattern recognition & decision making

Q1 . The following diagram represents a feed - forward neural network with one hidden layer . 3 5 2 4 The following table lists all the weights in the network . Each of the nodes 3 , 4 , 5 and 6 uses the following activation function ( v ) . W13 = -2 W35 = 1 W23 = 3 145 = -1 2014 4 36 = -1 1024 = -1 046 = 1 { 1 if v 20 0 otherwise where y denotes the weighted sum of a node . Each of the input nodes ( 1 and 2 ) can only receive binary values ( either 0 or 1 ) . Calculate the output of the network ( y5 and y6 ) for each of the input patterns : Input nodes Pattern Node 1 Node 2 P1 0 0 ( ) P2 1 Q2 . Explain how can we determine the optimum number of hidden nodes in a multilayer neural network ? Support your answer by references

Assignment 4 - ANN al. The Thes FI OL. The findingan mena fall man work with me hilelaget The following list the weights in the wok. Fach of the 1.45 alle tulewing where the steamed Lahti asterij Cik wewe want in the pas Lapu nodes Notes PI 11 1 Dr. Lina Al-Ebbini AME 446/2020 Assignment 4 - ANN Q1. The following diagram represents a feed forward neural network with one layer The following table lists all the weights in the network. Each of the modes 1,4,5 and 6 mes de following activation function (v) = -2 = 1 =- { 120 Otherwise = -1 = 1 where denotes the weighted sum of a node. Each of the input modes (nl) can only one values (either or 1). Calculate the output of the network by andy for each of the input Input odes Pattern Node Node 2 PI o 0 P2 1 0 02. Explow can we dumine the optimum where Assignment 4 - ANN al. The Thes FI OL. The findingan mena fall man work with me hilelaget The following list the weights in the wok. Fach of the 1.45 alle tulewing where the steamed Lahti asterij Cik wewe want in the pas Lapu nodes Notes PI 11 1 Dr. Lina Al-Ebbini AME 446/2020 Assignment 4 - ANN Q1. The following diagram represents a feed forward neural network with one layer The following table lists all the weights in the network. Each of the modes 1,4,5 and 6 mes de following activation function (v) = -2 = 1 =- { 120 Otherwise = -1 = 1 where denotes the weighted sum of a node. Each of the input modes (nl) can only one values (either or 1). Calculate the output of the network by andy for each of the input Input odes Pattern Node Node 2 PI o 0 P2 1 0 02. Explow can we dumine the optimum where