Question +1 -10 +1 20 -15 +10.a (1) -10 X1 10 (a (2) hw(x) 15 (a (1) -15 X2 +20 X1 X2 hw(x) 1 1 1 o 0 1 0 0 Given the simple neural network shown above and the input values in the table. a1, az are sigmoid activation. Fill in the output for each blank to classify each input as producing an output of either a 0 or a 1.
0UZG6H The Asker · Computer Science
Transcribed Image Text: +1 -10 +1 20 -15 +10.a (1) -10 X1 10 (a (2) hw(x) 15 (a (1) -15 X2 +20 X1 X2 hw(x) 1 1 1 o 0 1 0 0 Given the simple neural network shown above and the input values in the table. a1, az are sigmoid activation. Fill in the output for each blank to classify each input as producing an output of either a 0 or a 1.
More Transcribed Image Text: +1 -10 +1 20 -15 +10.a (1) -10 X1 10 (a (2) hw(x) 15 (a (1) -15 X2 +20 X1 X2 hw(x) 1 1 1 o 0 1 0 0 Given the simple neural network shown above and the input values in the table. a1, az are sigmoid activation. Fill in the output for each blank to classify each input as producing an output of either a 0 or a 1.
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4MY94N
The answer is given in the attached files.There are 3 layer, input layer, hidden layes and output layes.The hidden layes has 2 neurons a_(1) (1) and a_(2)(1).The output layes has 1 newros a,(2).{:[a_(1)(1)=+1(-10)+x_(1)(+10)+x_(2)(15)],[a_(2)(1)=+1(-15)+x_(1)(-10)+x_(2)(+20)]:}For x_(1)=1 and x_(2)=1 from the moput table,{:[a_(1)(1)=1(-10)+1(10)+1(15)=15],[a_(2)(1)=1(-15)+1(-10)+1(20)=-5.]:}Since a_(1) and a_(2) are sigonoidfunctions; the values cans ... See the full answer