Hi all,

I am currently working on Belief Propagation. I have a doubt while

estimating my beliefs. I need to estimate the r.v "xj's" of a vector "x"

i - function node

j -variable node

With some approximation, Message from function to variable node: Pi->j is

Gaussian and I have calculated its mean and variance.

Message from variable to function node: Pi<-j =P_x(xj) * Gaussian pdf (mean

and variance of this pdf known). Estimate of 'xj's' is the mean of the

distribution Pi<-j. I will then use this new estimate in next iteration and

repeat until convergence happens.

*I don't know how to calculate the mean and variance of Pi<-j =P_x(xj) *

Gaussian pdf . Here, **P_x(xj) = Gauss-Bernoulli Distribution*

*

*

Your reply would be of so much help!

Thanks a lot in advance

Regards,

Mahadevi