(adsbygoogle = window.adsbygoogle || []).push({}); 1. The problem statement, all variables and given/known data

Find the Corresponding normalization constants for the joint guassian

[tex]\\p\\(x,y) \alpha\ exp(-(ax^2/2) - (by^2/2) -cxy) [/tex]

ie: find P(x), P(y), and P(X,Y) normalization constants

relevant equations:

Mutual Information: M(x,y)

[tex]\\M(x,y) = \sum\\p(x,y)ln(p(x,y)/(p(x)*p(y)))[/tex]

3. The attempt at a solution

I've tried an integral over y then x but I end up with some messed up erf that I can't get rid of. My professor told me that the real point of this is that later we can use mutual information to get a ratio of the constants and that should equal [tex]\\1/2\\ln(1-c^2/ab)[/tex] but I haven't gotten anywhere close. I really just need a hint of where to start on this one as I have gotten nowhere with it any help is very appreciated.

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# Homework Help: Joint Probability/Mutual Information Normalization

Can you offer guidance or do you also need help?

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