I'm trying to understand Boltzmann machines. Tutorials explain it with two formulas.Logistic function for the probability of single units: $p(unit=1)=\frac{1}{1+e^{-\sum_{x}wx } }$and, when the machine is running, every state of the machine goes to the probability:$ p(State= state\ with\ energy\ E_i )=\frac{e^{-E_i}}{\sum_i e^{-E_i}} $so, the state depends on the units, and then if I understand correctly, the second formula is a consequence of the first; so, how can it be the proof that the distribution of $p(state)$ is a consequence of $p(unit)$?
boltzmann machine; from logistic function to boltzmann distribution
neural networks;deep learning;boltzmann machine