If you are given a neural network having an XOR topology:
x1 [A] weight(A,C)=1 weight(A,D)=1
[C] weight (C,D)=-2 [D]
x2 [B] weight(B,C)=1 weight(B,D)=1
Now XOR produces this truth table: T+T=F; T+F=T; F+T=T; F+F=F;
I am not allowed to change the network topology.
How should the weights and thresholds change to produce the negation of XOR? i.e T+T=T; T+F=F; F+T=F; F+F=T;
Do i just negate the weights and interchange the thresholds?
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