For your homework, update the weights for a second pattern 1.4>.2. Continue using the updated weights shown on the previous slide. Show your work like we did on the previous slide. Example 1-Setup - Assume a 2-2-1 network - All weights initialized to .5 - Learning rate set to 1 - Show updated weights after training on instance .9.60 - Show all net values, activations, outputs, and errors - Note: nodes 1 and 2 (input Zj=f( net j)=1+erti1 nodes) and 3 and 6 (bias f(netj)=Zj(1Zj) inputs) are just placeholder nodes and do not pass their values through a sigmoid. net4=.9.5+.6.5+1.5=1.25net5=1.25z4=1/(1+e1.25)=.777z5=.777net7=.777.5+.777.5+1.5=1.277z7=1/(1+e1.277)=.7827=(0.782).782(1.782)=.1334=(.133.5).777(1.777)=.01155=.0115w14=.5+(1.0115.9)=.4896w15=.4896w24=.5+(1.0115.6)=.4931w25=.4931w34=.5+(1.01151)=.4885w35=.4885w47=.5+(1.133.777)=.3964w57=.3964w67=.5+(1.1331)=.3667