Click here to Skip to main content
11,579,360 members (73,770 online)
Rate this: bad
good
Please Sign up or sign in to vote.
Hello,

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
                    T=1.5                                      T=0.5


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?
Posted 5-May-10 22:15pm
Edited 5-May-10 23:24pm
(no name)11.5K
v3

This content, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

  Print Answers RSS
0 OriginalGriff 1,003
1 Sergey Alexandrovich Kryukov 750
2 Abhinav S 583
3 F-ES Sitecore 420
4 Dave Kreskowiak 419


Advertise | Privacy | Mobile
Web04 | 2.8.150603.1 | Last Updated 6 May 2010
Copyright © CodeProject, 1999-2015
All Rights Reserved. Terms of Service
Layout: fixed | fluid

CodeProject, 503-250 Ferrand Drive Toronto Ontario, M3C 3G8 Canada +1 416-849-8900 x 100